66 citations · 80 across the 3 of their papers we have counts for
8 papers · 1 filter
Towards Lightweight Transformer via Group-wise Transformation for Vision-and-Language Tasks
Gen Luo, Yiyi Zhou, Xiaoshuai Sun +5
Despite the exciting performance, Transformer is criticized for its excessive parameters and computation cost. However, compressing Transformer remains as an open problem due to it…
ISTR: End-to-End Instance Segmentation with Transformers
Jie Hu, Liujuan Cao, Yao Lu +6
End-to-end paradigms significantly improve the accuracy of various deep-learning-based computer vision models. To this end, tasks like object detection have been upgraded by replac…
Network Pruning using Adaptive Exemplar Filters
Mingbao Lin, Rongrong Ji, Shaojie Li +4
Popular network pruning algorithms reduce redundant information by optimizing hand-crafted models, and may cause suboptimal performance and long time in selecting filters. We innov…
Rotated Binary Neural Network
Mingbao Lin, Rongrong Ji, Zihan Xu +5
Binary Neural Network (BNN) shows its predominance in reducing the complexity of deep neural networks. However, it suffers severe performance degradation. One of the major impedime…
HRank: Filter Pruning using High-Rank Feature Map
Mingbao Lin, Rongrong Ji, Yan Wang +4
Neural network pruning offers a promising prospect to facilitate deploying deep neural networks on resource-limited devices. However, existing methods are still challenged by the t…
Hadamard Codebook Based Deep Hashing
Shen Chen, Liujuan Cao, Mingbao Lin +5
As an approximate nearest neighbor search technique, hashing has been widely applied in large-scale image retrieval due to its excellent efficiency. Most supervised deep hashing me…