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Zero Shot Transfer Image Classification On 4

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Paper TitleRepository
BASIC (Lion)96.8--
CoCa96.5CoCa: Contrastive Captioners are Image-Text Foundation Models
LiT ViT-e96.1PaLI: A Jointly-Scaled Multilingual Language-Image Model
LiT-22B96.0Scaling Vision Transformers to 22 Billion Parameters
BASIC95.7Combined Scaling for Zero-shot Transfer Learning-
EVA-CLIP-18B95.7EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
EVA-CLIP-E/14+94.5EVA-CLIP: Improved Training Techniques for CLIP at Scale
LiT-tuning93.9LiT: Zero-Shot Transfer with Locked-image text Tuning
ALIGN92.2Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
CLIP88.9Learning Transferable Visual Models From Natural Language Supervision
AltCLIP87.2AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities
PaLI81.97PaLI: A Jointly-Scaled Multilingual Language-Image Model
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Zero Shot Transfer Image Classification On 4 | SOTA | HyperAI