activity
20162023
most citedDeep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification

31 citations · 45 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023

CVTHead: One-shot Controllable Head Avatar with Vertex-feature Transformer

Haoyu Ma, Tong Zhang, Shanlin Sun +3

Reconstructing personalized animatable head avatars has significant implications in the fields of AR/VR. Existing methods for achieving explicit face control of 3D Morphable Models…

cs.MM20232 cited

Improving Social Media Popularity Prediction with Multiple Post Dependencies

Zhizhen Zhang, Xiaohui Xie, Mengyu Yang +3

Social Media Popularity Prediction has drawn a lot of attention because of its profound impact on many different applications, such as recommendation systems and multimedia adverti…

cs.IR2023

T2Ranking: A large-scale Chinese Benchmark for Passage Ranking

Xiaohui Xie, Qian Dong, Bingning Wang +8

Passage ranking involves two stages: passage retrieval and passage re-ranking, which are important and challenging topics for both academics and industries in the area of Informati…

cs.CV2023

Localized Region Contrast for Enhancing Self-Supervised Learning in Medical Image Segmentation

Xiangyi Yan, Junayed Naushad, Chenyu You +6

Recent advancements in self-supervised learning have demonstrated that effective visual representations can be learned from unlabeled images. This has led to increased interest in…

cs.HC20226 cited

Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access System

Ziyi Ye, Xiaohui Xie, Yiqun Liu +4

With the growth of information on the Web, most users heavily rely on information access systems (e.g., search engines, recommender systems, etc.) in their daily lives. During this…

cs.IR20226 cited

Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval

Jingtao Zhan, Qingyao Ai, Yiqun Liu +4

Recent advance in Dense Retrieval (DR) techniques has significantly improved the effectiveness of first-stage retrieval. Trained with large-scale supervised data, DR models can enc…