DiffReID: Discriminative Diffusion Model for Object Re-Identification

arXiv:2609.36894 · cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.CV

Submitted: 2026-09-29

Updated: 2026-09-29

Comments: Accepted by TIP2026. More modifications can be performed

Code: https://github.com/AWangYQ/DiffReID

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Diffusion Model — 60× in this paper · explained in 8 episodes
• Diffusion Models — 35× in this paper · explained in 6 episodes
• Transformer — 18× in this paper · explained in 2 episodes
• Generalization — 16× in this paper · explained in 13 episodes
• Light Weight Denoiser — 7× in this paper
• Vision-guided Noise Generator — 7× in this paper
• Benchmark — 6× in this paper · explained in 2 episodes
• Feature Extraction — 6× in this paper · explained in 2 episodes
• Mutual Enhancement Constraint — 6× in this paper
• Regularization — 6× in this paper · explained in 3 episodes
• Representation Learning — 6× in this paper · explained in 2 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• KL Regularization — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Cosine Similarity — 4× in this paper · explained in 3 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Ablation Studies — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Contrastive Language-Image Pre-training — 2× in this paper
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Kullback-Leibler (KL) Divergence — 1× in this paper · explained in 3 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Mixture of Experts — 1× in this paper · explained in 2 episodes
• Temporal Condition Queries — 1× in this paper
• Two-stage training — 1× in this paper · explained in 2 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Auto-Encoding Variational Bayes
• Looking GLAMORous: Vehicle Re-Id in Heterogeneous Cameras Networks with Global and Local Attention
• Prototypical Contrastive Learning-based CLIP Fine-tuning for Object Re-identification

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