1.3k citations · 2.6k across the 51 of their papers we have counts for
11 papers · 1 filter
Learning to generate filters for convolutional neural networks
Wei Shen, Rujie Liu
Conventionally, convolutional neural networks (CNNs) process different images with the same set of filters. However, the variations in images pose a challenge to this fashion. In t…
Robust Face Detection via Learning Small Faces on Hard Images
Zhishuai Zhang, Wei Shen, Siyuan Qiao +3
Recent anchor-based deep face detectors have achieved promising performance, but they are still struggling to detect hard faces, such as small, blurred and partially occluded faces…
Tackling Early Sparse Gradients in Softmax Activation Using Leaky Squared Euclidean Distance
Wei Shen, Rujie Liu
Softmax activation is commonly used to output the probability distribution over categories based on certain distance metric. In scenarios like one-shot learning, the distance metri…
Generating Attention from Classifier Activations for Fine-grained Recognition
Wei Shen, Rujie Liu
Recent advances in fine-grained recognition utilize attention maps to localize objects of interest. Although there are many ways to generate attention maps, most of them rely on so…
PCL: Proposal Cluster Learning for Weakly Supervised Object Detection
Peng Tang, Xinggang Wang, Song Bai +4
Weakly Supervised Object Detection (WSOD), using only image-level annotations to train object detectors, is of growing importance in object recognition. In this paper, we propose a…
Resisting Large Data Variations via Introspective Transformation Network
Yunhan Zhao, Ye Tian, Charless Fowlkes +2
Training deep networks that generalize to a wide range of variations in test data is essential to building accurate and robust image classifiers. One standard strategy is to apply…