Research map / Vision-language and multimodal / Human and embodied modeling
Self-Supervised Learning of Visual Features Through Embedding Images Into Text Topic Spaces
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use image captions instead of noisy article text as the semantic supervision | TextTopicNet · PASCAL VOC2007 | %mAP image classification (fc7): 48.5 -> 55.4 | Helped |
| Concatenate TextTopicNet fc7 features with Sound fc7 features | TextTopicNet and Sound · PASCAL VOC2007 | %mAP image classification: 54.81% | Helped |
| Fine-tune the pretrained TextTopicNet CNN | TextTopicNet (Wiki) · STL-10 | accuracy: 66.00% -> 76.51% | Helped |
| Use article-derived topic distributions as supervision to learn visual features | TextTopicNet · PASCAL VOC2007 | %mAP image classification (pool5): 46.7 -> 47.4 | Helped |
| Use article-derived topic distributions as supervision to learn visual features | TextTopicNet · Wikipedia test | MAP average: 34.91 -> $38.87$ | Helped |
| Use article-derived topic distributions as supervision to learn visual features | TextTopicNet · PASCAL VOC2007 | %mAP object detection: 47.4 -> 43.0 | Hurt |
Closest papers by meaning
- Multi-Modal Representation Learning With Text-Driven Soft Masks (CVPR 2023 · similarity 0.90)
- T-MARS: Improving Visual Representations by Circumventing Text Feature Learning (ICLR 2024 · similarity 0.86)
- VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks (ICLR 2025 · similarity 0.86)
- TIPS: Text-Image Pretraining with Spatial awareness (ICLR 2025 · similarity 0.86)
- Linguistics-aware Masked Image Modeling for Self-supervised Scene Text Recognition (CVPR 2025 · similarity 0.85)
- Language-Assisted Image Clustering Guided by Discriminative Relational Signals and Adaptive Semantic Centers (NeurIPS 2026 · similarity 0.85)
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