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Chapter and Conference Paper
Adaptive Transformers for Robust Few-shot Cross-domain Face Anti-spoofing
While recent face anti-spoofing methods perform well under the intra-domain setups, an effective approach needs to account for much larger appearance variations of images acquired in complex scenes with differ...
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Chapter and Conference Paper
Progressive Refinement Network for Occluded Pedestrian Detection
We present Progressive Refinement Network (PRNet), a novel single-stage detector that tackles occluded pedestrian detection. Motivated by human’s progressive process on annotating occluded pedestrians, PRNet achi...
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Article
A Branch-and-Bound Framework for Unsupervised Common Event Discovery
Event discovery aims to discover a temporal segment of interest, such as human behavior, actions or activities. Most approaches to event discovery within or between time series use supervised learning. This be...
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Chapter and Conference Paper
Unsupervised Temporal Commonality Discovery
Unsupervised discovery of commonalities in images has recently attracted much interest due to the need to find correspondences in large amounts of visual data. A natural extension, and a relatively unexplored ...
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Chapter and Conference Paper
MOMI-Cosegmentation: Simultaneous Segmentation of Multiple Objects among Multiple Images
In this study, we introduce a new cosegmentation approach, MOMI-cosegmentation, to segment multiple objects that repeatedly appear among multiple images. The proposed approach tackles a more general problem than ...
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Chapter and Conference Paper
Heuristic Pre-clustering Relevance Feedback in Region-Based Image Retrieval
Relevance feedback (RF) and region-based image retrieval (RBIR) are two widely used methods to enhance the performance of content-based image retrieval (CBIR) systems. In this paper, these two methods are comb...
