2 citations · 2 across the 6 of their papers we have counts for
6 papers
Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model
Tao Lin, Yuxin Du, Jiting Liu +14
Vision-Language-Action models have emerged as a promising paradigm for robotic manipulation by unifying perception, language grounding, and action generation. However, they often s…
Focusable Monocular Depth Estimation
Yuxin Du, Tao Lin, Zile Zhong +7
Monocular depth foundation models generalize well across scenes, yet they are typically optimized with uniform pixel-wise objectives that do not distinguish user-specified or task-…
CAST: Collapse-Aware multi-Scale Topology Fusion for Multimodal Coreset Selection
Boran Zhao, Hetian Liu, Zhenxian Hu +3
The training of large multimodal models fundamentally relies on massive image-text datasets, which inevitably incur prohibitive computational overhead. Dataset selection offers a p…
ECHO: Continuous Hierarchical Memory for Vision-Language-Action Models
Yanbin Hu, Jin Cui, Jiayi Lu +6
Memory capacity is a critical factor determining the performance of Vision-Language-Action (VLA) models in long-horizon manipulation tasks. Existing memory-augmented architectures…
Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability
Xuelin Qian, Yu Wang, Simian Luo +9
Auto-regressive models have achieved impressive results in 2D image generation by modeling joint distributions in grid space. In this paper, we extend auto-regressive models to 3D…
Open-DDVM: A Reproduction and Extension of Diffusion Model for Optical Flow Estimation
Qiaole Dong, Bo Zhao, Yanwei Fu
Recently, Google proposes DDVM which for the first time demonstrates that a general diffusion model for image-to-image translation task works impressively well on optical flow esti…