activity
20152024
most citedLarge-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

53 citations · 200 across the 21 of their papers we have counts for

collaborators

36 papers

cs.CV2024

A Survey on Computational Solutions for Reconstructing Complete Objects by Reassembling Their Fractured Parts

Jiaxin Lu, Yongqing Liang, Huijun Han +4

Reconstructing a complete object from its parts is a fundamental problem in many scientific domains. The purpose of this article is to provide a systematic survey on this topic. Th…

cs.CV2024

MoGenTS: Motion Generation based on Spatial-Temporal Joint Modeling

Weihao Yuan, Weichao Shen, Yisheng He +5

Motion generation from discrete quantization offers many advantages over continuous regression, but at the cost of inevitable approximation errors. Previous methods usually quantiz…

cs.CV2024

Atlas Gaussians Diffusion for 3D Generation

Haitao Yang, Yuan Dong, Hanwen Jiang +3

Using the latent diffusion model has proven effective in developing novel 3D generation techniques. To harness the latent diffusion model, a key challenge is designing a high-fidel…

cs.CV20241 cited

Real3D: Scaling Up Large Reconstruction Models with Real-World Images

Hanwen Jiang, Qixing Huang, Georgios Pavlakos

The default strategy for training single-view Large Reconstruction Models (LRMs) follows the fully supervised route using large-scale datasets of synthetic 3D assets or multi-view…

cs.CV2024

OmniGlue: Generalizable Feature Matching with Foundation Model Guidance

Hanwen Jiang, Arjun Karpur, Bingyi Cao +2

The image matching field has been witnessing a continuous emergence of novel learnable feature matching techniques, with ever-improving performance on conventional benchmarks. Howe…

cs.CV2024

Freditor: High-Fidelity and Transferable NeRF Editing by Frequency Decomposition

Yisheng He, Weihao Yuan, Siyu Zhu +3

This paper enables high-fidelity, transferable NeRF editing by frequency decomposition. Recent NeRF editing pipelines lift 2D stylization results to 3D scenes while suffering from…