8 citations · 8 across the 8 of their papers we have counts for
8 papers
E2Pano: Learning Event-to-Panorama Image Reconstruction
Zhenyang Li, Zongqi He, Jia Pan +2
Event cameras offer microsecond-level temporal resolution and high dynamic range, potentially facilitating motion-blur-free panoramic imaging from fast rotational scanning. Nonethe…
ConsistNav: Closing the Action Consistency Gap in Zero-Shot Object Navigation with Semantic Executive Control
Haosen Wang, Zhenyang Li, Yinqiang Zhang +9
Zero-shot object navigation has advanced rapidly with open-vocabulary detectors, image--text models, and language-guided exploration. However, even after current methods detect a p…
PhysInOne: Visual Physics Learning and Reasoning in One Suite
Siyuan Zhou, Hejun Wang, Hu Cheng +36
We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike existing datasets limited to mere…
PhyGaP: Physically-Grounded Gaussians with Polarization Cues
Jiale Wu, Xiaoyang Bai, Zongqi He +2
Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated great success in modeling reflective 3D objects and their interaction with the environment via deferred rendering…
Enhancing Novel View Synthesis from extremely sparse views with SfM-free 3D Gaussian Splatting Framework
Zongqi He, Hanmin Li, Kin-Chung Chan +5
3D Gaussian Splatting (3DGS) has demonstrated remarkable real-time performance in novel view synthesis, yet its effectiveness relies heavily on dense multi-view inputs with precise…
See In Detail: Enhancing Sparse-view 3D Gaussian Splatting with Local Depth and Semantic Regularization
Zongqi He, Zhe Xiao, Kin-Chung Chan +3
3D Gaussian Splatting (3DGS) has shown remarkable performance in novel view synthesis. However, its rendering quality deteriorates with sparse inphut views, leading to distorted co…
Towards Multi-View Consistent Style Transfer with One-Step Diffusion via Vision Conditioning
Yushen Zuo, Jun Xiao, Kin-Chung Chan +5
The stylization of 3D scenes is an increasingly attractive topic in 3D vision. Although image style transfer has been extensively researched with promising results, directly applyi…
AIM 2024 Sparse Neural Rendering Challenge: Methods and Results
Michal Nazarczuk, Sibi Catley-Chandar, Thomas Tanay +27
This paper reviews the challenge on Sparse Neural Rendering that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2024. This manuscript…