5 papers
Uni3R: Unified 3D Reconstruction and Semantic Understanding via Generalizable Gaussian Splatting from Unposed Multi-View Images
Xiangyu Sun, Haoyi Jiang, Liu Liu +8
Reconstructing and semantically interpreting 3D scenes from sparse 2D views remains a fundamental challenge in computer vision. Conventional methods often decouple semantic underst…
UniLat3D: Geometry-Appearance Unified Latents for Single-Stage 3D Generation
Guanjun Wu, Jiemin Fang, Chen Yang +11
High-fidelity 3D asset generation is crucial for various industries. While recent 3D pretrained models show strong capability in producing realistic content, most are built upon di…
Snap-Snap: Taking Two Images to Reconstruct 3D Human Gaussians in Milliseconds
Jia Lu, Taoran Yi, Jiemin Fang +6
Reconstructing 3D human bodies from sparse views has been an appealing topic, which is crucial to broader the related applications. In this paper, we propose a quite challenging bu…
Dynamic 2D Gaussians: Geometrically Accurate Radiance Fields for Dynamic Objects
Shuai Zhang, Guanjun Wu, Zhoufeng Xie +3
Reconstructing objects and extracting high-quality surfaces play a vital role in the real world. Current 4D representations show the ability to render high-quality novel views for…
ViTGaze: Gaze Following with Interaction Features in Vision Transformers
Yuehao Song, Xinggang Wang, Jingfeng Yao +3
Gaze following aims to interpret human-scene interactions by predicting the person's focal point of gaze. Prevailing approaches often adopt a two-stage framework, whereby multi-mod…