activity
20192022
most citedTowards Interpretable and Robust Hand Detection via Pixel-wise Prediction

21 citations · 46 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV20229 cited

Multi-Granularity Alignment Domain Adaptation for Object Detection

Wenzhang Zhou, Dawei Du, Libo Zhang +2

Domain adaptive object detection is challenging due to distinctive data distribution between source domain and target domain. In this paper, we propose a unified multi-granularity…

cs.CV2022

End-to-End Compressed Video Representation Learning for Generic Event Boundary Detection

Congcong Li, Xinyao Wang, Longyin Wen +3

Generic event boundary detection aims to localize the generic, taxonomy-free event boundaries that segment videos into chunks. Existing methods typically require video frames to be…

cs.AI20201 cited

Learning to Infer User Hidden States for Online Sequential Advertising

Zhaoqing Peng, Junqi Jin, Lan Luo +11

To drive purchase in online advertising, it is of the advertiser's great interest to optimize the sequential advertising strategy whose performance and interpretability are both im…

cs.CV2020

Spatial Attention Pyramid Network for Unsupervised Domain Adaptation

Congcong Li, Dawei Du, Libo Zhang +4

Unsupervised domain adaptation is critical in various computer vision tasks, such as object detection, instance segmentation, and semantic segmentation, which aims to alleviate per…

cs.CV20209 cited

SiamMan: Siamese Motion-aware Network for Visual Tracking

Wenzhang Zhou, Longyin Wen, Libo Zhang +3

In this paper, we present a novel siamese motion-aware network (SiamMan) for visual tracking, which consists of the siamese feature extraction subnetwork, followed by the classific…

cs.CV202021 cited

Towards Interpretable and Robust Hand Detection via Pixel-wise Prediction

Dan Liu, Libo Zhang, Tiejian Luo +2

The lack of interpretability of existing CNN-based hand detection methods makes it difficult to understand the rationale behind their predictions. In this paper, we propose a novel…