SILC: Improving Vision Language Pretraining with Self-Distillation
Paper
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2310.13355
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Published
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4
Vision-Language
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Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper • 2310.16045 • Published • 13 -
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Paper • 2201.12086 • Published • 2 -
ImageNetVC: Zero-Shot Visual Commonsense Evaluation on 1000 ImageNet Categories
Paper • 2305.15028 • Published • 1 -
TiC-CLIP: Continual Training of CLIP Models
Paper • 2310.16226 • Published • 7 -
Segment Anything
Paper • 2304.02643 • Published • 2 -
MM-VID: Advancing Video Understanding with GPT-4V(ision)
Paper • 2310.19773 • Published • 18 -
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
Paper • 2310.19909 • Published • 19 -
Grounding Visual Illusions in Language: Do Vision-Language Models Perceive Illusions Like Humans?
Paper • 2311.00047 • Published • 7