5 papers
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…
HiFloat4 Format for Language Model Inference
Yuanyong Luo, Jing Huang, Yu Cheng +19
This paper introduces HiFloat4 (HiF4), a block floating-point data format tailored for deep learning. Each HiF4 unit packs 64 4-bit elements with 32 bits of shared scaling metadata…
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…
Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching
Xinyin Ma, Gongfan Fang, Michael Bi Mi +1
Diffusion Transformers have recently demonstrated unprecedented generative capabilities for various tasks. The encouraging results, however, come with the cost of slow inference, s…