27 citations · 51 across the 17 of their papers we have counts for
16 papers · 1 filter
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…
VideoLifter: Lifting Videos to 3D with Fast Hierarchical Stereo Alignment
Wenyan Cong, Hanqing Zhu, Kevin Wang +6
Efficiently reconstructing 3D scenes from monocular video remains a core challenge in computer vision, vital for applications in virtual reality, robotics, and scene understanding.…
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…
SiLK -- Simple Learned Keypoints
Pierre Gleize, Weiyao Wang, Matt Feiszli
Keypoint detection & descriptors are foundational tech-nologies for computer vision tasks like image matching, 3D reconstruction and visual odometry. Hand-engineered methods like H…
Open-world Instance Segmentation: Top-down Learning with Bottom-up Supervision
Tarun Kalluri, Weiyao Wang, Heng Wang +3
Many top-down architectures for instance segmentation achieve significant success when trained and tested on pre-defined closed-world taxonomy. However, when deployed in the open w…
EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset
Hao Tang, Kevin Liang, Matt Feiszli +1
Visual object tracking is a key component to many egocentric vision problems. However, the full spectrum of challenges of egocentric tracking faced by an embodied AI is underrepres…
RegCLR: A Self-Supervised Framework for Tabular Representation Learning in the Wild
Weiyao Wang, Byung-Hak Kim, Varun Ganapathi
Recent advances in self-supervised learning (SSL) using large models to learn visual representations from natural images are rapidly closing the gap between the results produced by…
Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity
Weiyao Wang, Matt Feiszli, Heng Wang +2
Open-world instance segmentation is the task of grouping pixels into object instances without any pre-determined taxonomy. This is challenging, as state-of-the-art methods rely on…
Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation
Weiyao Wang, Matt Feiszli, Heng Wang +1
Current state-of-the-art object detection and segmentation methods work well under the closed-world assumption. This closed-world setting assumes that the list of object categories…
Generic Event Boundary Detection: A Benchmark for Event Segmentation
Mike Zheng Shou, Stan Weixian Lei, Weiyao Wang +2
This paper presents a novel task together with a new benchmark for detecting generic, taxonomy-free event boundaries that segment a whole video into chunks. Conventional work in te…
What Makes Training Multi-Modal Classification Networks Hard?
Weiyao Wang, Du Tran, Matt Feiszli
Consider end-to-end training of a multi-modal vs. a single-modal network on a task with multiple input modalities: the multi-modal network receives more information, so it should m…