1 citations · 2 across the 8 of their papers we have counts for
8 papers
SAM 3D: 3Dfy Anything in Images
SAM 3D Team, Xingyu Chen, Fu-Jen Chu +20
We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single image. SAM 3D excels in natural images,…
Multi-SpatialMLLM: Multi-Frame Spatial Understanding with Multi-Modal Large Language Models
Runsen Xu, Weiyao Wang, Hao Tang +5
Multi-modal large language models (MLLMs) have rapidly advanced in visual tasks, yet their spatial understanding remains limited to single images, leaving them ill-suited for physi…
HOIGPT: Learning Long Sequence Hand-Object Interaction with Language Models
Mingzhen Huang, Fu-Jen Chu, Bugra Tekin +10
We introduce HOIGPT, a token-based generative method that unifies 3D hand-object interactions (HOI) perception and generation, offering the first comprehensive solution for caption…
Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
Jianing Yang, Alexander Sax, Kevin J. Liang +6
Multi-view 3D reconstruction remains a core challenge in computer vision, particularly in applications requiring accurate and scalable representations across diverse perspectives.…
OmniPose6D: Towards Short-Term Object Pose Tracking in Dynamic Scenes from Monocular RGB
Yunzhi Lin, Yipu Zhao, Fu-Jen Chu +6
To address the challenge of short-term object pose tracking in dynamic environments with monocular RGB input, we introduce a large-scale synthetic dataset OmniPose6D, crafted to mi…
ADen: Adaptive Density Representations for Sparse-view Camera Pose Estimation
Hao Tang, Weiyao Wang, Pierre Gleize +1
Recovering camera poses from a set of images is a foundational task in 3D computer vision, which powers key applications such as 3D scene/object reconstructions. Classic methods of…
3x2: 3D Object Part Segmentation by 2D Semantic Correspondences
Anh Thai, Weiyao Wang, Hao Tang +3
3D object part segmentation is essential in computer vision applications. While substantial progress has been made in 2D object part segmentation, the 3D counterpart has received l…
ICON: Incremental CONfidence for Joint Pose and Radiance Field Optimization
Weiyao Wang, Pierre Gleize, Hao Tang +3
Neural Radiance Fields (NeRF) exhibit remarkable performance for Novel View Synthesis (NVS) given a set of 2D images. However, NeRF training requires accurate camera pose for each…