Review on panoramic imaging and its applications in scene understanding
With the rapid development of high-speed communication and artificial intelligence
technologies, human perception of real-world scenes is no longer limited to the use of small …
technologies, human perception of real-world scenes is no longer limited to the use of small …
Vision-based semantic segmentation in scene understanding for autonomous driving: Recent achievements, challenges, and outlooks
Scene understanding plays a crucial role in autonomous driving by utilizing sensory data for
contextual information extraction and decision making. Beyond modeling advances, the …
contextual information extraction and decision making. Beyond modeling advances, the …
Clip2scene: Towards label-efficient 3d scene understanding by clip
Abstract Contrastive Language-Image Pre-training (CLIP) achieves promising results in 2D
zero-shot and few-shot learning. Despite the impressive performance in 2D, applying CLIP …
zero-shot and few-shot learning. Despite the impressive performance in 2D, applying CLIP …
Lasermix for semi-supervised lidar semantic segmentation
Densely annotating LiDAR point clouds is costly, which often restrains the scalability of fully-
supervised learning methods. In this work, we study the underexplored semi-supervised …
supervised learning methods. In this work, we study the underexplored semi-supervised …
Delivering arbitrary-modal semantic segmentation
Multimodal fusion can make semantic segmentation more robust. However, fusing an
arbitrary number of modalities remains underexplored. To delve into this problem, we create …
arbitrary number of modalities remains underexplored. To delve into this problem, we create …
Multi-modal data-efficient 3d scene understanding for autonomous driving
Efficient data utilization is crucial for advancing 3D scene understanding in autonomous
driving, where reliance on heavily human-annotated LiDAR point clouds challenges fully …
driving, where reliance on heavily human-annotated LiDAR point clouds challenges fully …
Segment any point cloud sequences by distilling vision foundation models
Recent advancements in vision foundation models (VFMs) have opened up new
possibilities for versatile and efficient visual perception. In this work, we introduce Seal, a …
possibilities for versatile and efficient visual perception. In this work, we introduce Seal, a …
Stpls3d: A large-scale synthetic and real aerial photogrammetry 3d point cloud dataset
Although various 3D datasets with different functions and scales have been proposed
recently, it remains challenging for individuals to complete the whole pipeline of large-scale …
recently, it remains challenging for individuals to complete the whole pipeline of large-scale …
3D semantic scene completion: A survey
L Roldao, R De Charette… - International Journal of …, 2022 - Springer
Semantic scene completion (SSC) aims to jointly estimate the complete geometry and
semantics of a scene, assuming partial sparse input. In the last years following the …
semantics of a scene, assuming partial sparse input. In the last years following the …
[HTML][HTML] Deep learning-based semantic segmentation of urban-scale 3D meshes in remote sensing: A survey
Semantic segmentation in 3D meshes is the classification of its constituent element (s) into
specific classes or categories. Using the powerful feature extraction abilities of deep neural …
specific classes or categories. Using the powerful feature extraction abilities of deep neural …