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Found 5 papers, 1 papers with code
Mitigate Domain Shift by Primary-Auxiliary Objectives Association for Generalizing Person ReID
While deep learning has significantly improved ReID model accuracy under the independent and identical distribution (IID) assumption, it has also become clear that such models degrade notably when applied to an unseen novel domain due to unpredictable/unknown domain shift.
Rapid Person Re-Identification via Sub-space Consistency Regularization
To strike a balance between the model accuracy and efficiency, we propose a novel Sub-space Consistency Regularization (SCR) algorithm that can speed up the ReID procedure by $0. 25$ times than real-value features under the same dimensions whilst maintaining a competitive accuracy, especially under short codes.
Feature-Distribution Perturbation and Calibration for Generalized Person ReID
In this work, we propose a Feature-Distribution Perturbation and Calibration (PECA) method to derive generic feature representations for person ReID, which is not only discriminative across cameras but also agnostic and deployable to arbitrary unseen target domains.
Local-Global Associative Frame Assemble in Video Re-ID
In this work, we explore jointly both local alignments and global correlations with further consideration of their mutual promotion/reinforcement so to better assemble complementary discriminative Re-ID information within all the relevant frames in video tracklets.
Gated Multiple Feedback Network for Image Super-Resolution
The rapid development of deep learning (DL) has driven single image super-resolution (SR) into a new era.
Ranked #18 on
Image Super-Resolution
on BSD100 - 4x upscaling
