Image Classification on Places 365
65.1Top-1 AccOmniVec2
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| OmniVec22025.07 | 65.1 | — | — | |
| OmniVec2025.07 | 63.5 | — | — | |
| InternImage2025.07 | 61.2 | — | — | |
| MetaFormer2025.07 | 60.7 | — | — | |
| MAEBackbone=ViT-H, Input Resolution=448, Pre-train Data=IN1K, Evaluation Protocol=Fine-tuned2021.11 | 60.3 | — | — | |
| Omnivore2025.07 | 59.9 | — | — | |
| MAEBackbone=ViT-H, Pre-train Data=IN1K, Evaluation Protocol=Fine-tuned2021.11 | 59.8 | — | — | |
| Omni-MAE2025.07 | 59.4 | — | — | |
| MAEBackbone=ViT-L, Pre-train Data=IN1K, Evaluation Protocol=Fine-tuned2021.11 | 59.4 | — | — | |
| EfficientNetBackbone=B82025.07 | 58.6 | — | — | |
| Previous bestPre-train Data=3.5 billion images2021.11 | 58 | — | — | |
| MAEBackbone=ViT-B, Pre-train Data=IN1K, Evaluation Protocol=Fine-tuned2021.11 | 57.9 | — | — | |
| SigLIP 2-B/16Evaluation Protocol=Linear Probe2026.05 | 56.18 | — | — | |
| VECA-B/16Evaluation Protocol=Linear Probe, Core tokens (C)=642026.05 | 55.82 | — | — | |
| DFNCLIP-B/16Evaluation Protocol=Linear Probe2026.05 | 55.79 | — | — | |
| DINOv3-B/16Evaluation Protocol=Linear Probe2026.05 | 55.39 | — | — | |
| OpenCLIP-B/16Evaluation Protocol=Linear Probe2026.05 | 55.35 | — | — | |
| VECA-B/16Evaluation Protocol=Linear Probe, Core tokens (C)=82026.05 | 55.3 | — | — | |
| CLIP-B/16Evaluation Protocol=Linear Probe2026.05 | 55.27 | — | — | |
| DINOv2-reg-B/14Evaluation Protocol=Linear Probe2026.05 | 54.81 | — | — | |
| AM-RADIOv2.5-B/16Evaluation Protocol=Linear Probe2026.05 | 54.13 | — | — | |
| DINOv2-B/14Evaluation Protocol=Linear Probe2026.05 | 53.37 | — | — | |
| SALF-CBMSparse final layer=false2025.02 | 49.38 | — | — | |
| StandardSparse final layer=false2025.02 | 48.56 | — | — | |
| SALF-CBMSparse final layer=true2025.02 | 46.73 | — | — | |
| LF-CBMSparse final layer=true2025.02 | 43.68 | — | — | |
| StandardSparse final layer=true2025.02 | 38.46 | — | — | |
| Individual NetworksBackbone=VGG-16, # Models=2, Size=1,074 MB2018.01 | — | 46.35 | 16.14 | |
| Jointly Trained NetworkBackbone=VGG-16, # Models=1, Size=537 MB2018.01 | — | 45.98 | 15.59 | |
| PackNetBackbone=VGG-16, # Models=1, Size=554 MB2018.01 | — | 46.64 | 15.92 | |
| PiggybackBackbone=VGG-16, # Models=1, Size=554 MB2018.01 | — | 46.71 | 16.18 |