10 citations · 13 across the 6 of their papers we have counts for
7 papers
Fast-VLA: You Only Think Once for Robot Manipulation
Kehong Gong, Guanli Hou, Xiaoxu Zheng +6
Vision-language-action (VLA) policies commonly place a multi-billion-parameter model inside the feedback loop, repeatedly recomputing task context whenever they predict a new actio…
Breaking the Horizontal Prior: From Long-Tailed Orientation Bias to Roll-Robust Monocular Depth Estimation
Kaihua Tang, Ziqing Xia, Xiaoxu Zheng +4
Despite recent advances in Monocular Depth Estimation, state-of-the-art depth foundation models remain vulnerable to robustness issues. Particularly, even slight camera rolls can r…
AnchorSplat: Feed-Forward 3D Gaussian Splatting with 3D Geometric Priors
Xiaoxue Zhang, Xiaoxu Zheng, Yixuan Yin +5
Recent feed-forward Gaussian reconstruction models adopt a pixel-aligned formulation that maps each 2D pixel to a 3D Gaussian, entangling Gaussian representations tightly with the…
WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion
Hanyang Kong, Xingyi Yang, Xiaoxu Zheng +1
Generating long-range, geometrically consistent video presents a fundamental dilemma: while consistency demands strict adherence to 3D geometry in pixel space, state-of-the-art gen…
GhostRNN: Reducing State Redundancy in RNN with Cheap Operations
Hang Zhou, Xiaoxu Zheng, Yunhe Wang +3
Recurrent neural network (RNNs) that are capable of modeling long-distance dependencies are widely used in various speech tasks, eg., keyword spotting (KWS) and speech enhancement…
Overcoming the Trade-off Between Accuracy and Plausibility in 3D Hand Shape Reconstruction
Ziwei Yu, Chen Li, Linlin Yang +4
Direct mesh fitting for 3D hand shape reconstruction is highly accurate. However, the reconstructed meshes are prone to artifacts and do not appear as plausible hand shapes. Conver…
Improving Deep Regression with Ordinal Entropy
Shihao Zhang, Linlin Yang, Michael Bi Mi +2
In computer vision, it is often observed that formulating regression problems as a classification task often yields better performance. We investigate this curious phenomenon and p…