Research map / Detection and segmentation / Open-set and few-shot detection
Disentangling Visual Embeddings for Attributes and Objects
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use GloVe instead of Fasttext embeddings (ablation) | OADis · MIT-States | AUC@1: 5.3 -> 5.9 | Helped |
| Combine GloVe with Fasttext embeddings instead of using GloVe alone (ablation) | OADis · MIT-States | AUC@1: 5.9 -> 5.5 | Hurt |
| Set lambda to 0.1 instead of 10 (ablation) | OADis · MIT-States | AUC@1: 5.9 -> 5.7 | Hurt |
| Set delta to 0.01 instead of 0.05 (ablation) | OADis · MIT-States | AUC@1: 5.9 -> 4.8 | Hurt |
| Set delta to 0.1 instead of 0.05 (ablation) | OADis · MIT-States | AUC@1: 5.9 -> 5.2 | Hurt |
| Set alpha1/alpha2 to 0.5 and alpha3/alpha4 to 0.1 rather than 0.05 (ablation) | OADis · MIT-States | AUC@1: 5.9 -> 5.3 | Hurt |
| Use an Object-Conditioned network rather than a Linear or MLP network (ablation) | OADis · MIT-States | AUC@1 | Helped |
Closest papers by meaning
- Beyond Seen Primitive Concepts and Attribute-Object Compositional Learning (CVPR 2024 · similarity 0.90)
- Attribute Prototype Network for Zero-Shot Learning (NeurIPS 2020 · similarity 0.90)
- Learning Conditional Attributes for Compositional Zero-Shot Learning (CVPR 2023 · similarity 0.90)
- VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learning (CVPR 2022 · similarity 0.89)
- TPR: Topology-Preserving Reservoirs for Generalized Zero-Shot Learning (NeurIPS 2024 · similarity 0.88)
- A Dynamic Learning Method towards Realistic Compositional Zero-Shot Learning (AAAI 2024 · similarity 0.88)
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