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Models/BLIP 2 (pretrained)

BLIP 2 (pretrained)

Reported on 6 benchmarks across 6 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology4 results

3DonOVAD-Box benchmark
mean average precision· uses extra data· 2023-01-30
25.5
best: 28 (X-VLM)
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597
2D ClassificationonOVAD-Box benchmark
mean average precision· uses extra data· 2023-01-30
25.5
best: 28 (X-VLM)
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597
2D Object DetectiononOVAD-Box benchmark
mean average precision· uses extra data· 2023-01-30
25.5
best: 28 (X-VLM)
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597
16konOVAD-Box benchmark
mean average precision· uses extra data· 2023-01-30
25.5
best: 28 (X-VLM)
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597

Computer Vision2 results

Object DetectiononOVAD-Box benchmark
mean average precision· uses extra data· 2023-01-30
25.5
best: 28 (X-VLM)
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597
Open Vocabulary Object DetectiononOVAD-Box benchmark
mean average precision· uses extra data· 2023-01-30
25.5
best: 28 (X-VLM)
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597