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by nielsr HF Staff - opened
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  1. README.md +4 -2
README.md CHANGED
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  ---
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  license: apache-2.0
 
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  tags:
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  - image-text-retrieval
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  - jepa
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  - contrastive-learning
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  - video-encoder
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  - pytorch
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- pipeline_tag: feature-extraction
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  ---
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  # scout-eccv-x-explora
@@ -15,6 +15,8 @@ Part of **SCOUT** (Sim-to-real Contrastive Outlier Understanding via Text), an E
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  paper on JEPA-based text-based person re-identification for the AI City Challenge Track 4 (Sim2Real).
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  Code: https://github.com/abtraore/SCOUT-ECCV
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  The paper's best single-model result: y-clip-v17 recipe + ExPLoRA-adapted X-encoder (partial block unfreeze + LoRA r=32 on the frozen V-JEPA2 ViT-L/16, selected via an Auto-RGN sensitivity probe) on top of a frozen CLIP-ViT-L/14 text tower.
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  - **Val mAP@10**: 0.9297
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  ## License
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  Apache 2.0 (see the source repo's LICENSE/NOTICE). This checkpoint does not redistribute any frozen
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- backbone weights, which carry their own upstream licenses.
 
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  ---
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  license: apache-2.0
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+ pipeline_tag: feature-extraction
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  tags:
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  - image-text-retrieval
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  - jepa
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  - contrastive-learning
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  - video-encoder
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  - pytorch
 
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  ---
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  # scout-eccv-x-explora
 
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  paper on JEPA-based text-based person re-identification for the AI City Challenge Track 4 (Sim2Real).
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  Code: https://github.com/abtraore/SCOUT-ECCV
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+ Paper: [SCOUT: Sim-to-Real Text-Based Person Retrieval by Embedding-Space Prediction over Frozen Video Features](https://huggingface.co/papers/2609.19483)
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+
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  The paper's best single-model result: y-clip-v17 recipe + ExPLoRA-adapted X-encoder (partial block unfreeze + LoRA r=32 on the frozen V-JEPA2 ViT-L/16, selected via an Auto-RGN sensitivity probe) on top of a frozen CLIP-ViT-L/14 text tower.
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  - **Val mAP@10**: 0.9297
 
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  ## License
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  Apache 2.0 (see the source repo's LICENSE/NOTICE). This checkpoint does not redistribute any frozen
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+ backbone weights, which carry their own upstream licenses.