434 citations · 2.1k across the 88 of their papers we have counts for
14 papers · 1 filter
General Greedy De-bias Learning
Xinzhe Han, Shuhui Wang, Chi Su +2
Neural networks often make predictions relying on the spurious correlations from the datasets rather than the intrinsic properties of the task of interest, facing sharp degradation…
Modeling Temporal Concept Receptive Field Dynamically for Untrimmed Video Analysis
Zhaobo Qi, Shuhui Wang, Chi Su +3
Event analysis in untrimmed videos has attracted increasing attention due to the application of cutting-edge techniques such as CNN. As a well studied property for CNN-based models…
Self-Regulated Learning for Egocentric Video Activity Anticipation
Zhaobo Qi, Shuhui Wang, Chi Su +3
Future activity anticipation is a challenging problem in egocentric vision. As a standard future activity anticipation paradigm, recursive sequence prediction suffers from the accu…
DVCFlow: Modeling Information Flow Towards Human-like Video Captioning
Xu Yan, Zhengcong Fei, Shuhui Wang +2
Dense video captioning (DVC) aims to generate multi-sentence descriptions to elucidate the multiple events in the video, which is challenging and demands visual consistency, discou…
Hierarchical Modular Network for Video Captioning
Hanhua Ye, Guorong Li, Yuankai Qi +3
Video captioning aims to generate natural language descriptions according to the content, where representation learning plays a crucial role. Existing methods are mainly developed…
Semi-Autoregressive Image Captioning
Xu Yan, Zhengcong Fei, Zekang Li +3
Current state-of-the-art approaches for image captioning typically adopt an autoregressive manner, i.e., generating descriptions word by word, which suffers from slow decoding issu…
Edge-featured Graph Neural Architecture Search
Shaofei Cai, Liang Li, Xinzhe Han +2
Graph neural networks (GNNs) have been successfully applied to learning representation on graphs in many relational tasks. Recently, researchers study neural architecture search (N…
Greedy Gradient Ensemble for Robust Visual Question Answering
Xinzhe Han, Shuhui Wang, Chi Su +2
Language bias is a critical issue in Visual Question Answering (VQA), where models often exploit dataset biases for the final decision without considering the image information. As…
Fast Batch Nuclear-norm Maximization and Minimization for Robust Domain Adaptation
Shuhao Cui, Shuhui Wang, Junbao Zhuo +3
Due to the domain discrepancy in visual domain adaptation, the performance of source model degrades when bumping into the high data density near decision boundary in target domain.…
Learning with Multiclass AUC: Theory and Algorithms
Zhiyong Yang, Qianqian Xu, Shilong Bao +2
The Area under the ROC curve (AUC) is a well-known ranking metric for problems such as imbalanced learning and recommender systems. The vast majority of existing AUC-optimization-b…
Poisoning Attack against Estimating from Pairwise Comparisons
Ke Ma, Qianqian Xu, Jinshan Zeng +2
As pairwise ranking becomes broadly employed for elections, sports competitions, recommendations, and so on, attackers have strong motivation and incentives to manipulate the ranki…
Location-Sensitive Visual Recognition with Cross-IOU Loss
Kaiwen Duan, Lingxi Xie, Honggang Qi +3
Object detection, instance segmentation, and pose estimation are popular visual recognition tasks which require localizing the object by internal or boundary landmarks. This paper…
Seeking the Shape of Sound: An Adaptive Framework for Learning Voice-Face Association
Peisong Wen, Qianqian Xu, Yangbangyan Jiang +3
Nowadays, we have witnessed the early progress on learning the association between voice and face automatically, which brings a new wave of studies to the computer vision community…
Rethinking Graph Neural Architecture Search from Message-passing
Shaofei Cai, Liang Li, Jincan Deng +4
Graph neural networks (GNNs) emerged recently as a standard toolkit for learning from data on graphs. Current GNN designing works depend on immense human expertise to explore diffe…