13 citations · 17 across the 8 of their papers we have counts for
8 papers
iDiT-HOI: Inpainting-based Hand Object Interaction Reenactment via Video Diffusion Transformer
Zhelun Shen, Chenming Wu, Junsheng Zhou +7
Digital human video generation is gaining traction in fields like education and e-commerce, driven by advancements in head-body animation and lip-syncing technologies. However, rea…
CMD: Constraining Multimodal Distribution for Domain Adaptation in Stereo Matching
Zhelun Shen, Zhuo Li, Chenming Wu +4
Recently, learning-based stereo matching methods have achieved great improvement in public benchmarks, where soft argmin and smooth L1 loss play a core contribution to their succes…
Splatter-360: Generalizable 360 Gaussian Splatting for Wide-baseline Panoramic Images
Zheng Chen, Chenming Wu, Zhelun Shen +5
Wide-baseline panoramic images are frequently used in applications like VR and simulations to minimize capturing labor costs and storage needs. However, synthesizing novel views fr…
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…
CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching
Zhelun Shen, Yuchao Dai, Zhibo Rao
Recently, the ever-increasing capacity of large-scale annotated datasets has led to profound progress in stereo matching. However, most of these successes are limited to a specific…
PCW-Net: Pyramid Combination and Warping Cost Volume for Stereo Matching
Zhelun Shen, Yuchao Dai, Xibin Song +3
Existing deep learning based stereo matching methods either focus on achieving optimal performances on the target dataset while with poor generalization for other datasets or focus…