11 papers
T2LDM++: A Self-Conditioned Representation Guided Diffusion Model for Realistic Text-to-LiDAR Scene Generation
Wentao Qu, Qi Zhang, Chenxu Wang +5
Recent progress in Text-to-Image generation benefits from large-scale Text-Image pairs. However, the scarcity of Text-LiDAR pairs often causes over-smoothed scenes and limited cont…
Reconstructing Close Human Interaction with Appearance and Proxemics Reasoning
Buzhen Huang, Chen Li, Chongyang Xu +4
Due to visual ambiguities and inter-person occlusions, existing human pose estimation methods cannot recover plausible close interactions from in-the-wild videos. Even state-of-the…
Generalizable Human Gaussians from Single-View Image
Jinnan Chen, Chen Li, Jianfeng Zhang +4
In this work, we tackle the task of learning 3D human Gaussians from a single image, focusing on recovering detailed appearance and geometry including unobserved regions. We introd…
MAR-3D: Progressive Masked Auto-regressor for High-Resolution 3D Generation
Jinnan Chen, Lingting Zhu, Zeyu Hu +4
Recent advances in auto-regressive transformers have revolutionized generative modeling across different domains, from language processing to visual generation, demonstrating remar…
DiHuR: Diffusion-Guided Generalizable Human Reconstruction
Jinnan Chen, Chen Li, Gim Hee Lee
We introduce DiHuR, a novel Diffusion-guided model for generalizable Human 3D Reconstruction and view synthesis from sparse, minimally overlapping images. While existing generaliza…
NeuSG: Neural Implicit Surface Reconstruction with 3D Gaussian Splatting Guidance
Hanlin Chen, Chen Li, Yunsong Wang +1
Existing neural implicit surface reconstruction methods have achieved impressive performance in multi-view 3D reconstruction by leveraging explicit geometry priors such as depth ma…