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Zero Shot Transfer Image Classification On 5

Metrics

Accuracy (Private)

Results

Performance results of various models on this benchmark

Paper Title
CoCa90.2CoCa: Contrastive Captioners are Image-Text Foundation Models
LiT-22B90.1Scaling Vision Transformers to 22 Billion Parameters
LiT ViT-e88.0PaLI: A Jointly-Scaled Multilingual Language-Image Model
EVA-CLIP-18B87.3EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
BASIC (Lion)86.4-
BASIC85.6Combined Scaling for Zero-shot Transfer Learning
InternVL-C83.8InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
EVA-CLIP-E/14+82.1EVA-CLIP: Improved Training Techniques for CLIP at Scale
LiT-tuning79.4LiT: Zero-Shot Transfer with Locked-image text Tuning
CLIP77.2Learning Transferable Visual Models From Natural Language Supervision
ALIGN75.8Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
AltCLIP69.5AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities
PaLI44.7PaLI: A Jointly-Scaled Multilingual Language-Image Model
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Zero Shot Transfer Image Classification On 5 | SOTA | HyperAI