Image Classification on ICinW 20 datasets 1.0 (test)
63.39AccuracyK-LITE
Evaluation Results
| Method | Links | |
|---|---|---|
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=28M (full), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 63.39 | |
| UniCLTraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=28M (full), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 60.99 | |
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Combine2022.04 | 60.72 | |
| UniCLTraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 59.04 | |
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=28M (full), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 58.56 | |
| UniCLTraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=27M (full), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 58.25 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=27M (full), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 58.24 | |
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 58.2 | |
| UniCLTraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=28M (full), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 57.92 | |
| K-LITETraining Dataset=ImageNet-21K, Number of Training Samples=13M (full), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 57.81 | |
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Combine2022.04 | 57.38 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=27M (full), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 57.06 | |
| UniCLTraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 56.45 | |
| UniCLTraining Dataset=ImageNet-21K, Number of Training Samples=13M (full), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 55.96 | |
| UniCLTraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=27M (full), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 55.96 | |
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 55.91 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 55.88 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Combine2022.04 | 54.28 | |
| K-LITETraining Dataset=ImageNet-21K, Number of Training Samples=13M (full), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 53.92 | |
| UniCLTraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 53.86 | |
| UniCLTraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 53.5 | |
| UniCLTraining Dataset=ImageNet-21K, Number of Training Samples=13M (full), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 53.07 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Fine-tuning, Few-shot setting=5-shot, Data Fusion Scheme=Combine2022.04 | 52.11 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Linear Probing, Few-shot setting=5-shot, Data Fusion Scheme=Concat2022.04 | 49.48 | |
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=28M (full), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 41.34 | |
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Combine2022.04 | 40.32 | |
| K-LITETraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 39.53 | |
| UniCLTraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=28M (full), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 38.9 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=27M (full), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 38.89 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 36.5 | |
| K-LITETraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Combine2022.04 | 36.5 | |
| UniCLTraining Dataset=GCC-15M + ImageNet-21K, Number of Training Samples=15M (half), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 36.31 | |
| UniCLTraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=27M (full), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 35.99 | |
| UniCLTraining Dataset=YFCC-14M + ImageNet-21K, Number of Training Samples=14M (half), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 34.3 | |
| K-LITETraining Dataset=ImageNet-21K, Number of Training Samples=13M (full), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 33.44 | |
| UniCLTraining Dataset=ImageNet-21K, Number of Training Samples=13M (full), Evaluation Protocol=Zero-shot, Data Fusion Scheme=Concat2022.04 | 27.15 |