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Found 7 papers, 2 papers with code
Fast Implicit Neural Representation Image Codec in Resource-limited Devices
With different parameter settings, our method can outperform popular AE-based codecs in constrained environments in terms of both quality and decoding time, or achieve state-of-the-art reconstruction quality compared to other INR codecs.
CLIP-based Synergistic Knowledge Transfer for Text-based Person Retrieval
Text-based Person Retrieval (TPR) aims to retrieve the target person images given a textual query.
Lifelong Person Re-Identification via Knowledge Refreshing and Consolidation
Lifelong person re-identification (LReID) is in significant demand for real-world development as a large amount of ReID data is captured from diverse locations over time and cannot be accessed at once inherently.
Controller-Guided Partial Label Consistency Regularization with Unlabeled Data
Partial label learning (PLL) learns from training examples each associated with multiple candidate labels, among which only one is valid.
Pose-guided Visible Part Matching for Occluded Person ReID
Occluded person re-identification is a challenging task as the appearance varies substantially with various obstacles, especially in the crowd scenario.
Deep Reinforcement Active Learning for Human-in-the-Loop Person Re-Identification
In particular, we formulate a Deep Reinforcement Active Learning (DRAL) method to guide an agent (a model in a reinforcement learning process) in selecting training samples on-the-fly by a human user/annotator.
Stepwise Metric Promotion for Unsupervised Video Person Re-Identification
The intensive annotation cost and the rich but unlabeled data contained in videos motivate us to propose an unsupervised video-based person re-identification (re-ID) method.
Ranked #7 on
Person Re-Identification
on PRID2011
