9 citations · 25 across the 16 of their papers we have counts for
14 papers · 1 filter
Digging into Depth Priors for Outdoor Neural Radiance Fields
Chen Wang, Jiadai Sun, Lina Liu +5
Neural Radiance Fields (NeRF) have demonstrated impressive performance in vision and graphics tasks, such as novel view synthesis and immersive reality. However, the shape-radiance…
MapNeRF: Incorporating Map Priors into Neural Radiance Fields for Driving View Simulation
Chenming Wu, Jiadai Sun, Zhelun Shen +1
Simulating camera sensors is a crucial task in autonomous driving. Although neural radiance fields are exceptional at synthesizing photorealistic views in driving simulations, they…
Digging Into Uncertainty-based Pseudo-label for Robust Stereo Matching
Zhelun Shen, Xibin Song, Yuchao Dai +3
Due to the domain differences and unbalanced disparity distribution across multiple datasets, current stereo matching approaches are commonly limited to a specific dataset and gene…
AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection
Zongdai Liu, Dingfu Zhou, Feixiang Lu +2
Existing deep learning-based approaches for monocular 3D object detection in autonomous driving often model the object as a rotated 3D cuboid while the object's geometric shape has…
Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation
Lina Liu, Xibin Song, Mengmeng Wang +2
Remarkable results have been achieved by DCNN based self-supervised depth estimation approaches. However, most of these approaches can only handle either day-time or night-time ima…
FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detection
Shaoqing Xu, Dingfu Zhou, Jin Fang +3
Accurate detection of obstacles in 3D is an essential task for autonomous driving and intelligent transportation. In this work, we propose a general multimodal fusion framework Fus…