Results 261 to 270 of about 9,013,010 (294)

Monocular 3D scene understanding with explicit occlusion reasoning

CVPR 2011, 2011
Scene understanding from a monocular, moving camera is a challenging problem with a number of applications including robotics and automotive safety. While recent systems have shown that this is best accomplished with a 3D scene model, handling of partial object occlusion is still unsatisfactory.
Christian Wojek, Stefan Walk, Stefan Roth 0001, Bernt Schiele   +3 more
openaire   +2 more sources

Stereoscopic Scene Flow Computation for 3D Motion Understanding

International Journal of Computer Vision, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Andreas Wedel, Thomas Brox, Tobi Vaudrey, Clemens Rabe, Uwe Franke, Daniel Cremers   +5 more
openaire   +3 more sources

3D reconstruction, omnidirectional vision and understanding of scenes

Procedings of the British Machine Vision Conference 2002, 2002
This text is related to the invited talk at the British Machine Vision Conference in Cardiff in September 2002 and highlights several recent contributions of our group to computer vision research. The aim is to hint the reader to several quite self-contained topics which we developed: omni-directional vision, scene reconstruction from images, and ...
openaire   +2 more sources

3D Scene Understanding with Deep Learning

2022
3D scene understanding is crucial for robotics, augmented reality and autonomous vehicles. In those applications, the 3D structure can be computed by using stereo cameras or depth sensors. One can process these 3D measurements using deep learning techniques to achieve remarkable performance in various perception related tasks.
openaire   +2 more sources

Coherent Scene Understanding With 3D Geometric Reasoning

2011
When looking at a single 2D image of a scene, humans could effortlessly understand the 3D world behind the scene even though stereo and motion cues are not available. Due to this remarkable human capability, one of the ultimate goals of computer vision is to enable machines to automatically infer the 3D structure of a scene given a single 2D image ...
openaire   +1 more source

LLaVA³: Representing 3D Scenes Like a Cubist Painter to Boost 3D Scene Understanding of VLMs

Proceedings of the AAAI Conference on Artificial Intelligence
Developing a multi-modal language model capable of understanding 3D scenes remains challenging due to the limited availability of 3D training data, in contrast to the abundance of 2D datasets used for vision-language models (VLMs). As an alternative, we introduce LLaVA³ (pronounced LLaVA Cube), a novel method that improves the 3D scene understanding ...
Doriand Petit, Steve Bourgeois, Vincent Gay-Bellile, Florian Chabot, Loïc Barthe   +4 more
openaire   +1 more source

Language-Assisted 3D Scene Understanding

IEEE Transactions on Multimedia
Yanmin Wu, Qiankun Gao, Renrui Zhang, Haijie Li, Jian Zhang 0018   +4 more
openaire   +1 more source

Deep Learning-Based Scene Understanding for Autonomous Robots: A Survey

Intelligence & Robotics, 2023
Yiyang Chen, Weidong Cao, Guangyi Tang
exaly  

MTANet: Multitask-Aware Network With Hierarchical Multimodal Fusion for RGB-T Urban Scene Understanding

IEEE Transactions on Intelligent Vehicles, 2023
Wujie Zhou, Jingsheng Lei, Shaohua Dong
exaly  

A Survey on Deep Learning Based Approaches for Scene Understanding in Autonomous Driving

Electronics, 2021
Hongjian Wei, Yingping Huang, Xing Hu
exaly