3 citations · 5 across the 5 of their papers we have counts for
6 papers
CanoVerse: 3D Object Scalable Canonicalization and Dataset for Generation and Pose
Li Jin, Yuchen Yang, Weikai Chen +11
3D learning systems implicitly assume that objects occupy a coherent reference frame. Nonetheless, in practice, every asset arrives with an arbitrary global rotation, and models ar…
Matrix3D: Large Photogrammetry Model All-in-One
Yuanxun Lu, Jingyang Zhang, Tian Fang +6
We present Matrix3D, a unified model that performs several photogrammetry subtasks, including pose estimation, depth prediction, and novel view synthesis using just the same model.…
Affine-based Deformable Attention and Selective Fusion for Semi-dense Matching
Hongkai Chen, Zixin Luo, Yurun Tian +8
Identifying robust and accurate correspondences across images is a fundamental problem in computer vision that enables various downstream tasks. Recent semi-dense matching methods…
Direct2.5: Diverse Text-to-3D Generation via Multi-view 2.5D Diffusion
Yuanxun Lu, Jingyang Zhang, Shiwei Li +6
Recent advances in generative AI have unveiled significant potential for the creation of 3D content. However, current methods either apply a pre-trained 2D diffusion model with the…
JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling
Jingyang Zhang, Shiwei Li, Yuanxun Lu +5
We introduce JointNet, a novel neural network architecture for modeling the joint distribution of images and an additional dense modality (e.g., depth maps). JointNet is extended f…
Learning Fully Dense Neural Networks for Image Semantic Segmentation
Mingmin Zhen, Jinglu Wang, Lei Zhou +2
Semantic segmentation is pixel-wise classification which retains critical spatial information. The "feature map reuse" has been commonly adopted in CNN based approaches to take adv…