3 citations · 7 across the 10 of their papers we have counts for
11 papers
Zero-P-to-3: Zero-Shot Partial-View Images to 3D Object
Yuxuan Lin, Ruihang Chu, Zhenyu Chen +9
Generative 3D reconstruction shows strong potential in incomplete observations. While sparse-view and single-image reconstruction are well-researched, partial observation remains u…
Direction-Aware Hybrid Representation Learning for 3D Hand Pose and Shape Estimation
Shiyong Liu, Zhihao Li, Xiao Tang +1
Most model-based 3D hand pose and shape estimation methods directly regress the parametric model parameters from an image to obtain 3D joints under weak supervision. However, these…
OccluGaussian: Occlusion-Aware Gaussian Splatting for Large Scene Reconstruction and Rendering
Shiyong Liu, Xiao Tang, Zhihao Li +6
In large-scale scene reconstruction using 3D Gaussian splatting, it is common to partition the scene into multiple smaller regions and reconstruct them individually. However, exist…
Decoupling Appearance Variations with 3D Consistent Features in Gaussian Splatting
Jiaqi Lin, Zhihao Li, Binxiao Huang +6
Gaussian Splatting has emerged as a prominent 3D representation in novel view synthesis, but it still suffers from appearance variations, which are caused by various factors, such…
MagicEraser: Erasing Any Objects via Semantics-Aware Control
Fan Li, Zixiao Zhang, Yi Huang +4
The traditional image inpainting task aims to restore corrupted regions by referencing surrounding background and foreground. However, the object erasure task, which is in increasi…
TraDiffusion: Trajectory-Based Training-Free Image Generation
Mingrui Wu, Oucheng Huang, Jiayi Ji +6
In this work, we propose a training-free, trajectory-based controllable T2I approach, termed TraDiffusion. This novel method allows users to effortlessly guide image generation via…
UniVoxel: Fast Inverse Rendering by Unified Voxelization of Scene Representation
Shuang Wu, Songlin Tang, Guangming Lu +2
Typical inverse rendering methods focus on learning implicit neural scene representations by modeling the geometry, materials and illumination separately, which entails significant…
MirrorGaussian: Reflecting 3D Gaussians for Reconstructing Mirror Reflections
Jiayue Liu, Xiao Tang, Freeman Cheng +9
3D Gaussian Splatting showcases notable advancements in photo-realistic and real-time novel view synthesis. However, it faces challenges in modeling mirror reflections, which exhib…
VastGaussian: Vast 3D Gaussians for Large Scene Reconstruction
Jiaqi Lin, Zhihao Li, Xiao Tang +8
Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed. While the recent 3D Gaussian Splatting works well on small-…
CoSeR: Bridging Image and Language for Cognitive Super-Resolution
Haoze Sun, Wenbo Li, Jianzhuang Liu +5
Existing super-resolution (SR) models primarily focus on restoring local texture details, often neglecting the global semantic information within the scene. This oversight can lead…
Learning Unorthogonalized Matrices for Rotation Estimation
Kerui Gu, Zhihao Li, Shiyong Liu +6
Estimating 3D rotations is a common procedure for 3D computer vision. The accuracy depends heavily on the rotation representation. One form of representation -- rotation matrices -…