TASK
DATASET
MODEL
METRIC NAME
METRIC VALUE
GLOBAL RANK
EXTRA DATA
REMOVE
Image Classification
ImageNet
CAFormer-B36 (384 res)
Top 1 Accuracy
86.4%
# 143
Image Classification
ImageNet
CAFormer-B36 (384 res)
Number of params
99M
# 861
Image Classification
ImageNet
CAFormer-B36 (384 res)
GFLOPs
72.2
# 440
Image Classification
ImageNet
ConvFormer-M36 (224 res, 21K)
Top 1 Accuracy
86.1%
# 170
Image Classification
ImageNet
ConvFormer-M36 (224 res, 21K)
Number of params
57M
# 755
Image Classification
ImageNet
ConvFormer-M36 (224 res, 21K)
GFLOPs
12.8
# 320
Image Classification
ImageNet
CAFormer-M36 (224 res, 21K)
Top 1 Accuracy
86.6%
# 132
Image Classification
ImageNet
CAFormer-M36 (224 res, 21K)
Number of params
56M
# 748
Image Classification
ImageNet
CAFormer-M36 (224 res, 21K)
GFLOPs
13.2
# 324
Image Classification
ImageNet
CAFormer-S36 (384 res, 21K)
Top 1 Accuracy
86.9%
# 115
Image Classification
ImageNet
CAFormer-S36 (384 res, 21K)
Number of params
39M
# 666
Image Classification
ImageNet
CAFormer-S36 (384 res, 21K)
GFLOPs
26.0
# 383
Image Classification
ImageNet
CAFormer-S36 (224 res, 21K)
Top 1 Accuracy
85.8%
# 187
Image Classification
ImageNet
CAFormer-S36 (224 res, 21K)
Number of params
39M
# 666
Image Classification
ImageNet
CAFormer-S36 (224 res, 21K)
GFLOPs
8.0
# 267
Image Classification
ImageNet
ConvFormer-S36 (384 res, 21K)
Top 1 Accuracy
86.4%
# 143
Image Classification
ImageNet
ConvFormer-S36 (384 res, 21K)
Number of params
40M
# 678
Image Classification
ImageNet
ConvFormer-S36 (384 res, 21K)
GFLOPs
22.4
# 371
Image Classification
ImageNet
ConvFormer-S36 (224 res, 21K)
Top 1 Accuracy
85.4%
# 221
Image Classification
ImageNet
ConvFormer-S36 (224 res, 21K)
Number of params
40M
# 678
Image Classification
ImageNet
ConvFormer-S36 (224 res, 21K)
GFLOPs
7.6
# 258
Image Classification
ImageNet
CAFormer-S18 (384 res, 21K)
Top 1 Accuracy
85.4%
# 221
Image Classification
ImageNet
CAFormer-S18 (384 res, 21K)
Number of params
26M
# 607
Image Classification
ImageNet
CAFormer-S18 (384 res, 21K)
GFLOPs
13.4
# 327
Image Classification
ImageNet
CAFormer-S18 (224 res, 21K)
Top 1 Accuracy
84.1%
# 325
Image Classification
ImageNet
CAFormer-S18 (224 res, 21K)
Number of params
26M
# 607
Image Classification
ImageNet
CAFormer-S18 (224 res, 21K)
GFLOPs
4.1
# 196
Image Classification
ImageNet
ConvFormer-S18 (384 res, 21K)
Top 1 Accuracy
85.0%
# 255
Image Classification
ImageNet
ConvFormer-S18 (384 res, 21K)
Number of params
27M
# 615
Image Classification
ImageNet
ConvFormer-S18 (384 res, 21K)
GFLOPs
11.6
# 311
Image Classification
ImageNet
ConvFormer-S18 (224 res, 21K)
Top 1 Accuracy
83.7%
# 365
Image Classification
ImageNet
ConvFormer-S18 (224 res, 21K)
Number of params
27M
# 615
Image Classification
ImageNet
ConvFormer-S18 (224 res, 21K)
GFLOPs
3.9
# 189
Image Classification
ImageNet
CAFormer-S18 (224 res)
Top 1 Accuracy
83.6%
# 378
Image Classification
ImageNet
CAFormer-S18 (224 res)
Number of params
26M
# 607
Image Classification
ImageNet
CAFormer-S18 (224 res)
GFLOPs
4.1
# 196
Image Classification
ImageNet
ConvFormer-B36 (224 res, 21K)
Top 1 Accuracy
87.0%
# 112
Image Classification
ImageNet
ConvFormer-B36 (224 res, 21K)
Number of params
100M
# 868
Image Classification
ImageNet
ConvFormer-B36 (224 res, 21K)
GFLOPs
22.6
# 373
Image Classification
ImageNet
ConvFormer-B36 (384 res, 21K)
Top 1 Accuracy
87.6%
# 84
Image Classification
ImageNet
ConvFormer-B36 (384 res, 21K)
Number of params
100M
# 868
Image Classification
ImageNet
ConvFormer-B36 (384 res, 21K)
GFLOPs
66.5
# 436
Image Classification
ImageNet
CAFormer-M36 (384 res)
Top 1 Accuracy
86.2%
# 164
Image Classification
ImageNet
CAFormer-M36 (384 res)
Number of params
56M
# 748
Image Classification
ImageNet
CAFormer-M36 (384 res)
GFLOPs
42.0
# 413
Image Classification
ImageNet
CAFormer-S36 (384 res)
Top 1 Accuracy
85.7%
# 200
Image Classification
ImageNet
CAFormer-S36 (384 res)
Number of params
39M
# 666
Image Classification
ImageNet
CAFormer-S36 (384 res)
GFLOPs
26.0
# 383
Image Classification
ImageNet
CAFormer-S36 (224 res)
Top 1 Accuracy
84.5%
# 293
Image Classification
ImageNet
CAFormer-S36 (224 res)
Number of params
39M
# 666
Image Classification
ImageNet
CAFormer-S36 (224 res)
GFLOPs
8.0
# 267
Image Classification
ImageNet
ConvFormer-S18 (224 res)
Top 1 Accuracy
83.0%
# 437
Image Classification
ImageNet
ConvFormer-S18 (224 res)
Number of params
27M
# 615
Image Classification
ImageNet
ConvFormer-S18 (224 res)
GFLOPs
3.9
# 189
Image Classification
ImageNet
ConvFormer-S36 (224 res)
Top 1 Accuracy
84.1%
# 325
Image Classification
ImageNet
ConvFormer-S36 (224 res)
Number of params
40M
# 678
Image Classification
ImageNet
ConvFormer-S36 (224 res)
GFLOPs
7.6
# 258
Image Classification
ImageNet
ConvFormer-S18 (384 res)
Top 1 Accuracy
84.4%
# 299
Image Classification
ImageNet
ConvFormer-S18 (384 res)
Number of params
27M
# 615
Image Classification
ImageNet
ConvFormer-S18 (384 res)
GFLOPs
11.6
# 311
Image Classification
ImageNet
ConvFormer-M36 (224 res)
Top 1 Accuracy
84.5%
# 293
Image Classification
ImageNet
ConvFormer-M36 (224 res)
Number of params
57M
# 755
Image Classification
ImageNet
ConvFormer-M36 (224 res)
GFLOPs
12.8
# 320
Image Classification
ImageNet
CAFormer-S18 (384 res)
Top 1 Accuracy
85.0%
# 255
Image Classification
ImageNet
CAFormer-S18 (384 res)
Number of params
26M
# 607
Image Classification
ImageNet
CAFormer-S18 (384 res)
GFLOPs
13.4
# 327
Image Classification
ImageNet
CAFormer-M36 (224 res)
Top 1 Accuracy
85.2%
# 239
Image Classification
ImageNet
CAFormer-M36 (224 res)
Number of params
56M
# 748
Image Classification
ImageNet
CAFormer-M36 (224 res)
GFLOPs
13.2
# 324
Image Classification
ImageNet
ConvFormer-S36 (384 res)
Top 1 Accuracy
85.4%
# 221
Image Classification
ImageNet
ConvFormer-S36 (384 res)
Number of params
40M
# 678
Image Classification
ImageNet
ConvFormer-S36 (384 res)
GFLOPs
22.4
# 371
Image Classification
ImageNet
ConvFormer-M36 (384 res)
Top 1 Accuracy
85.6%
# 209
Image Classification
ImageNet
ConvFormer-M36 (384 res)
Number of params
57M
# 755
Image Classification
ImageNet
ConvFormer-M36 (384 res)
GFLOPs
37.7
# 407
Image Classification
ImageNet
ConvFormer-B36 (224 res)
Top 1 Accuracy
84.8%
# 270
Image Classification
ImageNet
ConvFormer-B36 (224 res)
Number of params
100M
# 868
Image Classification
ImageNet
ConvFormer-B36 (224 res)
GFLOPs
22.6
# 373
Image Classification
ImageNet
CAFormer-B36 (224 res)
Top 1 Accuracy
85.5%
# 212
Image Classification
ImageNet
CAFormer-B36 (224 res)
Number of params
99M
# 861
Image Classification
ImageNet
CAFormer-B36 (224 res)
GFLOPs
23.2
# 375
Image Classification
ImageNet
ConvFormer-B36 (384 res)
Top 1 Accuracy
85.7%
# 200
Image Classification
ImageNet
ConvFormer-B36 (384 res)
Number of params
100M
# 868
Image Classification
ImageNet
ConvFormer-B36 (384 res)
GFLOPs
66.5
# 436
Image Classification
ImageNet
CAFormer-B36 (384 res, 21K)
Top 1 Accuracy
88.1%
# 67
Image Classification
ImageNet
CAFormer-B36 (384 res, 21K)
Number of params
99M
# 861
Image Classification
ImageNet
CAFormer-B36 (384 res, 21K)
GFLOPs
72.2
# 440
Image Classification
ImageNet
CAFormer-B36 (224 res, 21K)
Top 1 Accuracy
87.4%
# 93
Image Classification
ImageNet
CAFormer-B36 (224 res, 21K)
Number of params
99M
# 861
Image Classification
ImageNet
CAFormer-B36 (224 res, 21K)
GFLOPs
23.2
# 375
Image Classification
ImageNet
CAFormer-M36 (384 res, 21K)
Top 1 Accuracy
87.5%
# 86
Image Classification
ImageNet
CAFormer-M36 (384 res, 21K)
Number of params
56M
# 748
Image Classification
ImageNet
CAFormer-M36 (384 res, 21K)
GFLOPs
42
# 413
Image Classification
ImageNet
ConvFormer-M36 (384 res, 21K)
Top 1 Accuracy
86.9%
# 115
Image Classification
ImageNet
ConvFormer-M36 (384 res, 21K)
Number of params
57M
# 755
Image Classification
ImageNet
ConvFormer-M36 (384 res, 21K)
GFLOPs
37.7
# 407
Domain Generalization
ImageNet-A
ConvFormer-B36 (384)
Top-1 accuracy %
55.3
# 17
Domain Generalization
ImageNet-A
CAFormer-B36 (IN-21K)
Top-1 accuracy %
69.4
# 9
Domain Generalization
ImageNet-A
CAFormer-B36 (IN-21K, 384)
Top-1 accuracy %
79.5
# 5
Domain Generalization
ImageNet-A
ConvFormer-B36 (IN-21K)
Top-1 accuracy %
63.3
# 12
Domain Generalization
ImageNet-A
ConvFormer-B36 (IN-21K, 384)
Top-1 accuracy %
73.5
# 8
Domain Generalization
ImageNet-A
CAFormer-B36
Top-1 accuracy %
48.5
# 20
Domain Generalization
ImageNet-A
CAFormer-B36 (384)
Top-1 accuracy %
61.9
# 14
Domain Generalization
ImageNet-A
ConvFormer-B36
Top-1 accuracy %
40.1
# 23
Domain Generalization
ImageNet-C
CAFormer-B36 (IN21K, 384)
mean Corruption Error (mCE)
30.8
# 2
Domain Generalization
ImageNet-C
CAFormer-B36
mean Corruption Error (mCE)
42.6
# 18
Domain Generalization
ImageNet-C
ConvFormer-B36 (IN21K)
mean Corruption Error (mCE)
35.0
# 7
Domain Generalization
ImageNet-C
CAFormer-B36 (IN21K)
mean Corruption Error (mCE)
31.8
# 5
Domain Generalization
ImageNet-C
ConvFormer-B36
mean Corruption Error (mCE)
46.3
# 23
Domain Generalization
ImageNet-R
CAFormer-B36 (IN21K, 384)
Top-1 Error Rate
29.6
# 5
Domain Generalization
ImageNet-R
CAFormer-B36 (IN21K)
Top-1 Error Rate
31.7
# 7
Domain Generalization
ImageNet-R
ConvFormer-B36
Top-1 Error Rate
48.9
# 25
Domain Generalization
ImageNet-R
ConvFormer-B36 (384)
Top-1 Error Rate
47.8
# 24
Domain Generalization
ImageNet-R
CAFormer-B36 (384)
Top-1 Error Rate
45
# 21
Domain Generalization
ImageNet-R
CAFormer-B36
Top-1 Error Rate
46.1
# 23
Domain Generalization
ImageNet-R
ConvFormer-B36 (IN21K, 384)
Top-1 Error Rate
33.5
# 10
Domain Generalization
ImageNet-R
ConvFormer-B36 (IN21K)
Top-1 Error Rate
34.7
# 13
Domain Generalization
ImageNet-Sketch
ConvFormer-B36 (IN21K, 384)
Top-1 accuracy
52.9
# 7
Domain Generalization
ImageNet-Sketch
CAFormer-B36
Top-1 accuracy
42.5
# 17
Domain Generalization
ImageNet-Sketch
ConvFormer-B36
Top-1 accuracy
39.5
# 19
Domain Generalization
ImageNet-Sketch
CAFormer-B36 (IN21K, 384)
Top-1 accuracy
54.5
# 5
Domain Generalization
ImageNet-Sketch
ConvFormer-B36 (IN21K)
Top-1 accuracy
52.7
# 9
Domain Generalization
ImageNet-Sketch
CAFormer-B36 (IN21K)
Top-1 accuracy
52.8
# 8