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Found 7 papers, 5 papers with code
Learning Intra and Inter-Camera Invariance for Isolated Camera Supervised Person Re-identification
To eliminate the confounding effect of camera bias, we propose to learn both intra- and inter-camera invariance under a unified framework.
Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification
To this end, we build a dual-branch network architecture based upon a modified Vision Transformer (ViT).
Offline-Online Associated Camera-Aware Proxies for Unsupervised Person Re-identification
Assisted with the camera-aware proxies, we design two proxy-level contrastive learning losses that are, respectively, based on offline and online association results.
Camera-aware Proxies for Unsupervised Person Re-Identification
These camera-aware proxies enable us to deal with large intra-ID variance and generate more reliable pseudo labels for learning.
The DeepFake Detection Challenge (DFDC) Dataset
In addition to Deepfakes, a variety of GAN-based face swapping methods have also been published with accompanying code.
Towards Precise Intra-camera Supervised Person Re-identification
Our approach performs even comparable to state-of-the-art fully supervised methods in two of the datasets.
Deep Active Learning for Video-based Person Re-identification
With the gained annotations of the actively selected candidates, the tracklets' pesudo labels are updated by label merging and further used to re-train our re-ID model.
