13 citations · 49 across the 17 of their papers we have counts for
17 papers
Joint Correcting and Refinement for Balanced Low-Light Image Enhancement
Nana Yu, Hong Shi, Yahong Han
Low-light image enhancement tasks demand an appropriate balance among brightness, color, and illumination. While existing methods often focus on one aspect of the image without con…
Weakly-Supervised Video Anomaly Detection with Snippet Anomalous Attention
Yidan Fan, Yongxin Yu, Wenhuan Lu +1
With a focus on abnormal events contained within untrimmed videos, there is increasing interest among researchers in video anomaly detection. Among different video anomaly detectio…
Prototype-guided Cross-task Knowledge Distillation for Large-scale Models
Deng Li, Aming Wu, Yahong Han +1
Recently, large-scale pre-trained models have shown their advantages in many tasks. However, due to the huge computational complexity and storage requirements, it is challenging to…
Peng Cheng Object Detection Benchmark for Smart City
Yaowei Wang, Zhouxin Yang, Rui Liu +4
Object detection is an algorithm that recognizes and locates the objects in the image and has a wide range of applications in the visual understanding of complex urban scenes. Exis…
Action Keypoint Network for Efficient Video Recognition
Xu Chen, Yahong Han, Xiaohan Wang +2
Reducing redundancy is crucial for improving the efficiency of video recognition models. An effective approach is to select informative content from the holistic video, yielding a…
Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection
Rui Liu, Yahong Han, Yaowei Wang +1
Domain adaptive object detection (DAOD) aims to improve the generalization ability of detectors when the training and test data are from different domains. Considering the signific…
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal
Yucheng Shi, Yahong Han, Yu-an Tan +1
Vision transformers (ViTs) have demonstrated impressive performance and stronger adversarial robustness compared to Convolutional Neural Networks (CNNs). On the one hand, ViTs' foc…
Domain Adaptation without Model Transferring
Kunhong Wu, Yucheng Shi, Yahong Han +3
In recent years, researchers have been paying increasing attention to the threats brought by deep learning models to data security and privacy, especially in the field of domain ad…
Vector-Decomposed Disentanglement for Domain-Invariant Object Detection
Aming Wu, Rui Liu, Yahong Han +2
To improve the generalization of detectors, for domain adaptive object detection (DAOD), recent advances mainly explore aligning feature-level distributions between the source and…
Exploring Uncertainty in Deep Learning for Construction of Prediction Intervals
Yuandu Lai, Yucheng Shi, Yahong Han +3
Deep learning has achieved impressive performance on many tasks in recent years. However, it has been found that it is still not enough for deep neural networks to provide only poi…
Anomaly Detection with Prototype-Guided Discriminative Latent Embeddings
Yuandu Lai, Yahong Han, Yaowei Wang
Recent efforts towards video anomaly detection (VAD) try to learn a deep autoencoder to describe normal event patterns with small reconstruction errors. The video inputs with large…
Universal-Prototype Enhancing for Few-Shot Object Detection
Aming Wu, Yahong Han, Linchao Zhu +1
Few-shot object detection (FSOD) aims to strengthen the performance of novel object detection with few labeled samples. To alleviate the constraint of few samples, enhancing the ge…
Hierarchical Memory Decoding for Video Captioning
Aming Wu, Yahong Han
Recent advances of video captioning often employ a recurrent neural network (RNN) as the decoder. However, RNN is prone to diluting long-term information. Recent works have demonst…
Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement
Aming Wu, Yahong Han, Linchao Zhu +1
Most state-of-the-art methods of object detection suffer from poor generalization ability when the training and test data are from different domains, e.g., with different styles. T…
Curls & Whey: Boosting Black-Box Adversarial Attacks
Yucheng Shi, Siyu Wang, Yahong Han
Image classifiers based on deep neural networks suffer from harassment caused by adversarial examples. Two defects exist in black-box iterative attacks that generate adversarial ex…
Movie Question Answering: Remembering the Textual Cues for Layered Visual Contents
Bo Wang, Youjiang Xu, Yahong Han +1
Movies provide us with a mass of visual content as well as attracting stories. Existing methods have illustrated that understanding movie stories through only visual content is sti…
Pooling the Convolutional Layers in Deep ConvNets for Action Recognition
Shichao Zhao, Yanbin Liu, Yahong Han +1
Deep ConvNets have shown its good performance in image classification tasks. However it still remains as a problem in deep video representation for action recognition. The problem…