140 citations · 166 across the 7 of their papers we have counts for
7 papers
KernelWarehouse: Towards Parameter-Efficient Dynamic Convolution
Chao Li, Anbang Yao
Dynamic convolution learns a linear mixture of static kernels weighted with their sample-dependent attentions, demonstrating superior performance compared to normal convolution…
Ske2Grid: Skeleton-to-Grid Representation Learning for Action Recognition
Dongqi Cai, Yangyuxuan Kang, Anbang Yao +1
This paper presents Ske2Grid, a new representation learning framework for improved skeleton-based action recognition. In Ske2Grid, we define a regular convolution operation upon a…
NORM: Knowledge Distillation via N-to-One Representation Matching
Xiaolong Liu, Lujun Li, Chao Li +1
Existing feature distillation methods commonly adopt the One-to-one Representation Matching between any pre-selected teacher-student layer pair. In this paper, we present N-to-One…
Compacting Binary Neural Networks by Sparse Kernel Selection
Yikai Wang, Wenbing Huang, Yinpeng Dong +2
Binary Neural Network (BNN) represents convolution weights with 1-bit values, which enhances the efficiency of storage and computation. This paper is motivated by a previously reve…
3D Human Pose Lifting with Grid Convolution
Yangyuxuan Kang, Yuyang Liu, Anbang Yao +2
Existing lifting networks for regressing 3D human poses from 2D single-view poses are typically constructed with linear layers based on graph-structured representation learning. In…
Efficient Meta-Tuning for Content-aware Neural Video Delivery
Xiaoqi Li, Jiaming Liu, Shizun Wang +6
Recently, Deep Neural Networks (DNNs) are utilized to reduce the bandwidth and improve the quality of Internet video delivery. Existing methods train corresponding content-aware su…