ML Research Wiki / Benchmarks / Model Compression / ImageNet

ImageNet

Model Compression Benchmark

Performance Over Time

📊 Showing 12 results | 📏 Metric: Top-1

Top Performing Models

Rank Model Paper Top-1 Date Code
1 ADLIK-MO-ResNet50+W4A4 Learned Step Size Quantization 77.88 2019-02-21 📦 zhutmost/lsq-net 📦 hustzxd/LSQuantization 📦 ZouJiu1/LSQplus
2 ADLIK-MO-ResNet50+W3A4 Learned Step Size Quantization 77.34 2019-02-21 📦 zhutmost/lsq-net 📦 hustzxd/LSQuantization 📦 ZouJiu1/LSQplus
3 ResNet-18 + 4bit-1dim model compression using DKM R2 Loss: Range Restriction Loss for Model Compression and Quantization 70.52 2023-03-14 -
4 MobileNet-v1 + 4bit-1dim model compression using DKM R2 Loss: Range Restriction Loss for Model Compression and Quantization 69.63 2023-03-14 -
5 ResNet-18 + 2bit-1dim model compression using DKM R2 Loss: Range Restriction Loss for Model Compression and Quantization 68.63 2023-03-14 -
6 MobileNet-v1 + 2bit-1dim model compression using DKM R2 Loss: Range Restriction Loss for Model Compression and Quantization 67.62 2023-03-14 -
7 ResNet-18 + 4bit-4dim model compression using DKM R2 Loss: Range Restriction Loss for Model Compression and Quantization 66.10 2023-03-14 -
8 ResNet-18 + 2bit-2dim model compression using DKM R2 Loss: Range Restriction Loss for Model Compression and Quantization 64.70 2023-03-14 -
9 MobileNet-v1 + 4bit-4dim model compression using DKM R2 Loss: Range Restriction Loss for Model Compression and Quantization 61.40 2023-03-14 -
10 ResNet-18 + 1bit-1dim model compression using DKM R2 Loss: Range Restriction Loss for Model Compression and Quantization 59.70 2023-03-14 -

All Papers (12)

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
ResNet-18 + 4bit-1dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
MobileNet-v1 + 4bit-1dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
ResNet-18 + 2bit-1dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
MobileNet-v1 + 2bit-1dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
ResNet-18 + 4bit-4dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
ResNet-18 + 2bit-2dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
MobileNet-v1 + 4bit-4dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
ResNet-18 + 1bit-1dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
MobileNet-v1 + 2bit-2dim model compression using DKM

R2 Loss: Range Restriction Loss for Model Compression and Quantization

2023
MobileNet-v1 + 1bit-1dim model compression using DKM