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Add new publications, restructure GAIA videos, and fix format
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‎_pages/projects/gaia.md‎

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height: 100%;
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object-fit: cover;
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}
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</style>
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</head>
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<div class="container" style="overflow: hidden;">
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<div style="width: 33%; float: left;margin-bottom: 20px; text-align: center;">
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<div style="width: 33%; float: left;margin-bottom: 20px; text-align: center;">
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<a href="http://www.urjc.es">
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<img style="max-width: 60%; height: auto; margin-bottom: 10px;" src="https://upload.wikimedia.org/wikipedia/commons/thumb/8/84/URJC_logo.svg/2560px-URJC_logo.svg.png" alt="">
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<img style="max-width: 60%; height: auto; margin-bottom: 10px;" src="https://upload.wikimedia.org/wikipedia/commons/thumb/8/84/URJC_logo.svg/2560px-URJC_logo.svg.png" alt="">
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</a>
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</div>
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<div style="width: 33%; float: left; margin-bottom: 20px; text-align: center;">
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<div style="width: 33%; float: left; margin-bottom: 20px; text-align: center;">
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<a href="https://roboticslaburjc.github.io/">
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<img style="max-width: 30%; height: auto; margin-bottom: 10px;" src="https://pbs.twimg.com/profile_images/1709157413134188544/MHuOqgeK_400x400.jpg" alt="">
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<img style="max-width: 30%; height: auto; margin-bottom: 10px;" src="https://pbs.twimg.com/profile_images/1709157413134188544/MHuOqgeK_400x400.jpg" alt="">
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</a>
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</div>
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<div style="width: 33%; float: left; margin-bottom: 100px; text-align: center;">
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<img style="max-width: 33%; height: auto; margin-bottom: 10px;" src="/assets/images/lines/gaia.jpg" alt="">
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<div style="width: 33%; float: left; margin-bottom: 100px; text-align: center;">
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<img style="max-width: 33%; height: auto; margin-bottom: 10px;" src="/assets/images/lines/gaia.jpg" alt="">
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</div>
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The main 3 contributions of the RoboticsLab group are:
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<b> * LIDAR Signal Densification Algorithms:</b> Research focuses on algorithms and software techniques for densifying the LIDAR sensor signal, commonly used in outdoor robots.
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<b> * LIDAR Signal Densification Algorithms:</b> Research focuses on algorithms and software techniques for densifying the LIDAR sensor signal, commonly used in outdoor robots.
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<b> * Outdoor Navigation Algorithms:</b> This involves developing and evaluating point-to-point autonomous navigation algorithms for robots in unstructured environments, such as forests.
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<b> * Outdoor Navigation Algorithms:</b> This involves developing and evaluating point-to-point autonomous navigation algorithms for robots in unstructured environments, such as forests.
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<b> * Deep Learning for Object and Surface Detection:</b> Evolution of techniques for detecting objects and surfaces in unstructured environments using Deep Learning and sensors like LIDAR and visual cameras, aimed at autonomous robot navigation.
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<b> * Deep Learning for Object and Surface Detection:</b> Evolution of techniques for detecting objects and surfaces in unstructured environments using Deep Learning and sensors like LIDAR and visual cameras, aimed at autonomous robot navigation.
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<div style="display: flex; justify-content: space-around; align-items: flex-start;">
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<div style="width: 70%; float: left; margin-bottom: 100px; text-align: center;">
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<img style="max-width: 70%; height: auto; margin-bottom: 10px;" src="https://gaia-project.es/media/uploads/bloques/general_/bosque__en_llamas.jpg" alt="">
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<div style="width: 70%; float: left; margin-bottom: 100px; text-align: center;">
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<img style="max-width: 70%; height: auto; margin-bottom: 10px;" src="https://gaia-project.es/media/uploads/bloques/general_/bosque__en_llamas.jpg" alt="">
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</div>
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</div>
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## Videos
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### Lidar Segmentation
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### LiDAR Segmentation
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<div class="swiper mySwiper">
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<div class="swiper-wrapper">
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<div class="swiper-slide">
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<iframe
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id="video-lidar-1"
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id="video-lidar-3"
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width="560"
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height="315"
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src="https://www.youtube.com/embed/MCsIj0M7fzM?enablejsapi=1&rel=0&modestbranding=1"
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src="https://www.youtube.com/embed/AcJvDmwYneQ?enablejsapi=1&rel=0&modestbranding=1"
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title="YouTube video player"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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</div>
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<div class="swiper-slide">
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<iframe
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id="video-liDAR-2"
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id="video-lidar-2"
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width="560"
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height="315"
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src="https://www.youtube.com/embed/qwk5qm3bDOw?enablejsapi=1&rel=0&modestbranding=1"
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</div>
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<div class="swiper-slide">
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<iframe
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id="video-lidar-3"
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id="video-lidar-1"
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width="560"
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height="315"
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src="https://www.youtube.com/embed/AcJvDmwYneQ?enablejsapi=1&rel=0&modestbranding=1"
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src="https://www.youtube.com/embed/MCsIj0M7fzM?enablejsapi=1&rel=0&modestbranding=1"
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title="YouTube video player"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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<div class="swiper-pagination"></div>
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</div>
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### Environments and Visual Segmentation
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### Image Segmentation
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<div class="swiper mySwiper">
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<div class="swiper-wrapper">
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<div class="swiper-slide">
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<iframe
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id="video-env-1"
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id="video-img-1"
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width="560"
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height="315"
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src="https://www.youtube.com/embed/Zoy12gF2pFw?enablejsapi=1&rel=0&modestbranding=1"
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src="https://www.youtube.com/embed/pZQ4GW4Rv3E?enablejsapi=1&rel=0&modestbranding=1"
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title="YouTube video player"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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allowfullscreen>
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</iframe>
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</div>
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</div>
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<div class="swiper-button-next"></div>
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<div class="swiper-button-prev"></div>
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<div class="swiper-pagination"></div>
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</div>
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### Simulated Environments
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<div class="swiper mySwiper">
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<div class="swiper-wrapper">
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<div class="swiper-slide">
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<iframe
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id="video-env-2"
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id="video-env-4"
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width="560"
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height="315"
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src="https://www.youtube.com/embed/ySQJ98mw5pQ?enablejsapi=1&rel=0&modestbranding=1"
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src="https://www.youtube.com/embed/W-XWX9uMyDU?enablejsapi=1&rel=0&modestbranding=1"
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title="YouTube video player"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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id="video-env-3"
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width="560"
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src="https://www.youtube.com/embed/ZRoQ_49oX1k?enablejsapi=1&rel=0&modestbranding=1"
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src="https://www.youtube.com/embed/Zoy12gF2pFw?enablejsapi=1&rel=0&modestbranding=1"
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title="YouTube video player"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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id="video-env-2"
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src="https://www.youtube.com/embed/W-XWX9uMyDU?enablejsapi=1&rel=0&modestbranding=1"
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src="https://www.youtube.com/embed/ySQJ98mw5pQ?enablejsapi=1&rel=0&modestbranding=1"
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title="YouTube video player"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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id="video-env-1"
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src="https://www.youtube.com/embed/pZQ4GW4Rv3E?enablejsapi=1&rel=0&modestbranding=1"
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src="https://www.youtube.com/embed/ZRoQ_49oX1k?enablejsapi=1&rel=0&modestbranding=1"
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title="YouTube video player"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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allowfullscreen>
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</div>
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<div class="swiper-wrapper">
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id="video-trash-1"
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id="video-trash-2"
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src="https://www.youtube.com/embed/E3NFhQJKh64?enablejsapi=1&rel=0&modestbranding=1"
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id="video-trash-1"
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},
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},
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});
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// Cargar la API de YouTube
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function onYouTubeIframeAPIReady() {
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// YouTube IFrames ya estarán listos
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firstScriptTag.parentNode.insertBefore(tag, firstScriptTag);
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</script>
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<!--
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<!--
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<div style="display: flex; justify-content: space-around; align-items: flex-start;">
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<div style="width: 60%; text-align: center; padding: 10px;">
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<div style="width: 60%; text-align: center; padding: 10px;">
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<h2>Real-Time 3D Lidar Visualizer</h2>
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<iframe width="560" height="315" src="https://www.youtube.com/embed/qwk5qm3bDOw?si=vETtTTi4hGcqeiGt" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
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</div>
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<div style="width: 60%; text-align: center; padding: 10px;">
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<div style="width: 60%; text-align: center; padding: 10px;">
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<h2>Realistic Unstructured environment v3</h2>
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<iframe width="560" height="315" src="https://www.youtube.com/embed/Zoy12gF2pFw?si=UcfMKxeauzWipMyf" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
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<div style="width: 60%; text-align: center; padding: 10px;">
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<h2>Unstructured environment v2</h2>
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<iframe width="560" height="315" src="https://www.youtube.com/embed/ySQJ98mw5pQ?si=yR3h9Cu_G6WgOkjS" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
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<div style="width: 60%; text-align: center; padding: 10px;">
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<h2>Unstructured environment</h2>
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<iframe width="560" height="315" src="https://www.youtube.com/embed/ZRoQ_49oX1k?si=eto7gPZoU0TwweIQ" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
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## Publications
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<div style="display: flex; justify-content: space-around; max-width: 1200px; margin: auto;">
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<div style="background-color: #f2f2f2; box-shadow: -8px 0 15px -3px rgba(0, 0, 0, 0.1); padding: 20px; margin: 10px; flex: 1;">
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<div style="font-size: 18px; font-weight: bold; margin-bottom: 5px;">Cross-Dataset Evaluation of Visual Semantic Segmentation Models for Off-Road Autonomous Driving</div>
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<div style="font-size: 16px; color: #555; margin-bottom: 5px;">David Pascual-Hernández, Sergio Paniego, Roberto Calvo-Palomino, Inmaculada Mora-Jiménez, Jose Maria Cañas-Plaza</div>
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<div style="font-size: 14px; color: #555;">Expert Systems with Applications, Elsevier, 2026</div>
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</div>
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<div style="background-color: #f2f2f2; box-shadow: -8px 0 15px -3px rgba(0, 0, 0, 0.1); padding: 20px; margin: 10px; flex: 1;">
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<div style="font-size: 18px; font-weight: bold; margin-bottom: 5px;">Deep Learning-Based Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving in Unstructured Environments</div>
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<div style="font-size: 16px; color: #555; margin-bottom: 5px;"> Félix Martínez, David Pascual-Hernández, Daniel Borja Fernández, Inmaculada Mora Jiménez, José María Cañas</div>
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<div style="font-size: 14px; color: #555;">Proceedings of the XXV International Workshop on Physical Agents (WAF), 2025</div>
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</div>
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</div>
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<div style="font-size: 14px; color: #555;">SoftwareX, Elsevier, 2024</div>
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</div>
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## Founded by
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<div class="container" style="overflow: hidden;">
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<div style="width: 100%; float: left;margin-bottom: 20px; text-align: center;">
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<img style="max-width: 100%; height: auto; margin-bottom: 10px;" src="/assets/images/lines/gaia_founded.png" alt="Paper">
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<img style="max-width: 100%; height: auto; margin-bottom: 10px;" src="/assets/images/lines/gaia_founded.png" alt="Paper">
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</div>

‎_pages/publications/2026/cross_dataset_evaluation_of_visual_semantic_segmentation_models_for_off_road_autonomous_driving.md‎

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---
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permalink: /publications/2026/cross_dataset_evaluation_of_visual_semantic_segmentation_models_for_off_road_autonomous_driving
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title: "Cross-dataset Evaluation of Visual Semantic Segmentation Models for Off-road Autonomous Driving"
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layout: single
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classes: wide
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---
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<p style="text-align: center; font-weight: bold;">Neurocomputing, 2024</p>
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<p style="text-align: center"><a href="https://sergiopaniego.github.io/">David Pascual-Hernández<sup>1</sup></a>, <a href="https://sergiopaniego.github.io/">Sergio Paniego<sup>1</sup></a>, <a href="https://servicios.urjc.es/pdi/ver/roberto.calvo">Roberto Calvo-Palomino<sup>1</sup></a></p>, <a href="https://servicios.urjc.es/pdi/ver/inmaculada.mora">Inmaculada Mora-Jiménez<sup>1</sup></a></p>, <a href="https://gsyc.urjc.es/jmplaza/">Jose Maria Cañas-Plaza<sup>1</sup></a></p>
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<div class="container" style="overflow: hidden;">
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<p style="text-align: center; width: 50%; float: left;">1: <a href="https://www.urjc.es/"><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/8/84/URJC_logo.svg/1280px-URJC_logo.svg.png" width="40%" height="40%" alt="URJC"/></a></p>
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</div>
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<p style="text-align: center">DOI: <a href="https://doi.org/10.1016/j.eswa.2026.132656">10.1016/j.eswa.2026.132656</a></p>
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## Abstract
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Intelligent autonomous driving in off-road environments is an emerging field with great potential to impact areas such as agriculture, forestry, and rescue operations. Perception in these scenarios presents unique challenges due to the diversity of elements and weather conditions, along with the inherent ambiguity in class definitions. Consequently, off-road visual semantic segmentation datasets remain underdeveloped, roughly ten times smaller than their urban counterparts, hindering dependable performance assessment and potentially compromising the safety of autonomous systems. To address these challenges, we present a comprehensive cross-dataset evaluation of visual semantic segmentation models for autonomous off-road navigation. We propose a unified ontology that harmonizes class definitions across relevant datasets, enabling their combination for both training and testing. This approach ensures fair model comparisons and reliable assessment of generalization to unseen domains. We further benchmark models on the original datasets, analyze the impact of different ontology harmonization criteria and conversion strategies, and evaluate the trade-off between segmentation performance and computational cost. Results show that Transformer-based architectures achieve the most consistent segmentation performance across datasets. While often computationally demanding, some variants maintain real-time inference (≈12 ms) with top-tier accuracy. The unified ontology simplifies the segmentation task, yielding more reliable models and about 40% faster training convergence. Cross-dataset training further enhances generalization, improving mean IoU by up to +20% on RUGD and +13% on WildScenes compared to RELLIS-3D-only training. Overall, this study provides valuable insights for developing robust perception modules for off-road autonomous vehicles.
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<div style="display: flex;justify-content: space-around;margin-bottom: 20px;">
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<div style="width: 45%;">
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<img src="https://ars.els-cdn.com/content/image/1-s2.0-S0957417426015691-gr2_lrg.jpg" frameborder="0" allowfullscreen></img>
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</div>
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<div style="width: 45%;">
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<img src="https://ars.els-cdn.com/content/image/1-s2.0-S0957417426015691-gr11_lrg.jpg" frameborder="0" allowfullscreen></img>
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</div>
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</div>
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## Materials
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<div class="container" style="overflow: hidden;">
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<div style="width: 33%; float: left;margin-bottom: 20px; text-align: center;">
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<a href="https://doi.org/10.1016/j.eswa.2026.132656">
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<img style="max-width: 30%; height: auto; margin-bottom: 10px;" src="https://cdn-icons-png.flaticon.com/512/3731/3731553.png" alt="Paper">
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<p>Paper</p>
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</a>
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</div>
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<div style="width: 33%; float: left;margin-bottom: 20px; text-align: center;">
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<a href="https://github.com/JdeRobot/PerceptionMetrics">
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<img style="max-width: 30%; height: auto; margin-bottom: 10px;" src="https://static.thenounproject.com/png/1448954-200.png" alt="Code">
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<p>Evaluation Code</p>
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</a>
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</div>
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<div style="width: 33%; float: left;margin-bottom: 20px; text-align: center;">
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<a href="https://huggingface.co/roboticslaburjc-org/cross-dataset-visual-offroad-segmentation">
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<img style="max-width: 30%; height: auto; margin-bottom: 10px;" src="https://cdn-icons-png.flaticon.com/512/6461/6461819.png" alt="Models' weights">
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<p>Models' weights</p>
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</a>
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</div>
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</div>
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## Citation
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```
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@article{pascual2026cross,
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title={Cross-Dataset Evaluation of Visual Semantic Segmentation Models for Off-Road Autonomous Driving},
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author={Pascual-Hern{\'a}ndez, David and Paniego, Sergio and Calvo-Palomino, Roberto and Mora-Jim{\'e}nez, Inmaculada and Ca{\~n}as-Plaza, Jos{\'e} Mar{\'\i}a},
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journal={Expert Systems with Applications},
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pages={132656},
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year={2026},
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publisher={Elsevier}
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}
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```

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