87 citations · 376 across the 31 of their papers we have counts for
7 papers · 1 filter
Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning
Bin Li, Yin Li, Kevin W. Eliceiri
We address the challenging problem of whole slide image (WSI) classification. WSIs have very high resolutions and usually lack localized annotations. WSI classification can be cast…
ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles
Ran Xu, Chen-lin Zhang, Pengcheng Wang +5
Advanced video analytic systems, including scene classification and object detection, have seen widespread success in various domains such as smart cities and autonomous transporta…
Comprehensive Image Captioning via Scene Graph Decomposition
Yiwu Zhong, Liwei Wang, Jianshu Chen +2
We address the challenging problem of image captioning by revisiting the representation of image scene graph. At the core of our method lies the decomposition of a scene graph into…
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation
Liwei Wang, Jing Huang, Yin Li +3
Weakly supervised phrase grounding aims at learning region-phrase correspondences using only image-sentence pairs. A major challenge thus lies in the missing links between image re…
In the Eye of the Beholder: Gaze and Actions in First Person Video
Yin Li, Miao Liu, James M. Rehg
We address the task of jointly determining what a person is doing and where they are looking based on the analysis of video captured by a headworn camera. To facilitate our researc…
Interpretable and Accurate Fine-grained Recognition via Region Grouping
Zixuan Huang, Yin Li
We present an interpretable deep model for fine-grained visual recognition. At the core of our method lies the integration of region-based part discovery and attribution within a d…
Gradients as Features for Deep Representation Learning
Fangzhou Mu, Yingyu Liang, Yin Li
We address the challenging problem of deep representation learning--the efficient adaption of a pre-trained deep network to different tasks. Specifically, we propose to explore gra…