7 papers
Syn4D: A Multiview Synthetic 4D Dataset
Zeren Jiang, Yushi Lan, Yihang Luo +8
Dense 3D reconstruction and tracking of dynamic scenes from monocular video remains an important open challenge in computer vision. Progress in this area has been constrained by th…
VLANeXt: Recipes for Building Strong VLA Models
Xiao-Ming Wu, Bin Fan, Kang Liao +6
Following the rise of large foundation models, Vision-Language-Action models (VLAs) emerged, leveraging strong visual and language understanding from Vision-Language Models for gen…
4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere
Yihang Luo, Shangchen Zhou, Yushi Lan +2
We present 4RC, a unified feed-forward framework for 4D reconstruction from monocular videos. Unlike existing approaches that typically decouple motion from geometry or produce lim…
OmniVGGT: Omni-Modality Driven Visual Geometry Grounded Transformer
Haosong Peng, Hao Li, Yalun Dai +8
General 3D foundation models have started to lead the trend of unifying diverse vision tasks, yet most assume RGB-only inputs and ignore readily available geometric cues (e.g., cam…
STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer
Yushi Lan, Yihang Luo, Fangzhou Hong +7
We present STream3R, a novel approach to 3D reconstruction that reformulates pointmap prediction as a decoder-only Transformer problem. Existing state-of-the-art methods for multi-…
3DEnhancer: Consistent Multi-View Diffusion for 3D Enhancement
Yihang Luo, Shangchen Zhou, Yushi Lan +2
Despite advances in neural rendering, due to the scarcity of high-quality 3D datasets and the inherent limitations of multi-view diffusion models, view synthesis and 3D model gener…