Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("tong.Coggan2024_behavior-ConditionWiseAccuracySimilarity")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.844
2	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.779
3	convnext_large_imagenet_full_seed-0	.700
4	vit_base_patch16_clip_224:openai_ft_in1k	.677
5	cvt_cvt-21-384-in1k_4_LucyV4	.659
6	convnext_xlarge:fb_in22k_ft_in1k	.636
7	focalnet_tiny_lrf_in1k	.628
8	cvt_cvt-21-224-in1k_4_LucyV4	.626
9	convnext_base_imagenet_full_seed-0	.619
10	convnext_tiny:in12k_ft_in1k	.613
11	vit_relpos_base_patch16_clsgap_224:sw_in1k	.611
12	convnext_large:fb_in22k_ft_in1k	.603
13	AdvProp_efficientnet-b7	.597
14	tv_efficientnet-b1	.595
15	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.591
16	resnet50-VITO-8deg-cc	.590
17	resnet50-vitoimagevidnet8	.590
18	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.588
19	resnet101_ecoset_full	.588
20	cvt_cvt-13-224-in1k_4_LucyV4	.586
21	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.575
22	effnetb1_272x240	.573
23	resnet152_ecoset_full	.571
24	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.566
25	AdvProp_efficientnet-b6	.558
26	omnivore_swinS	.555
27	resnext101_32x8d_wsl	.554
28	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.552
29	AT_efficientnet-b2	.552
30	AdvProp_efficientnet-b2	.552
31	efficientnet-b7	.551
32	ViT_L_32_imagenet1k	.542
33	resnet_101_v2	.541
34	convnext_small_imagenet_full_seed-0	.540
35	resnext101_32x48d_wsl	.536
36	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.535
37	resnext101_32x16d_wsl	.534
38	convnext_tiny_imagenet_full_seed-0	.529
39	vit_large_patch14_clip_224:openai_ft_in1k	.526
40	deit_large_imagenet_full_seed-0	.523
41	convnext_tiny_sup	.519
42	resnet_50_v2	.515
43	resnet50-moclr8deg	.515
44	vit_large_patch14_clip_224:laion2b_ft_in1k	.505
45	resnet50_ecoset_full	.504
46	cvt_cvt-13-384-in1k_4_LucyV4	.501
47	AdvProp_efficientnet-b8	.497
48	BiT-S-R50x1	.482
49	resnet_152_v2	.478
50	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.476
51	deit_base_imagenet_full_seed-0	.471
52	resnext101_32x32d_wsl	.469
53	resnet-152_v2_pytorch	.466
54	efficientnet_b0	.463
55	resnet152_imagenet_full	.459
56	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.457
57	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.453
58	AdvProp_efficientnet-b4	.448
59	deit_small_imagenet_full_seed-0	.448
60	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.446
61	convnext_femto_ols:d1_in1k	.434
62	inception_v3	.430
63	grcnn_109	.425
64	voneresnet-50	.421
65	densenet_201_pytorch	.412
66	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.411
67	yolos_tiny	.409
68	antialiased-r50	.409
69	resnet50_tutorial	.407
70	voneresnet-50-non_stochastic	.398
71	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.393
72	resnet_50_v1_spiking_l4a	.392
73	nasnet_large	.383
74	resnet_50_v1_spiking	.383
75	BiT-S-R101x1	.379
76	convnext_small_imagenet_100_seed-0	.374
77	inception_v4	.372
78	blt_vs	.372
79	Res2Net50_26w_4s	.371
80	resnet_152_v1	.371
81	inception_v3_pytorch	.360
82	yudixie_resnet50_imagenet1kpret_0_240908	.359
83	resnet18_ecoset_full	.356
84	resnet_101_v1	.351
85	resnet34_ecoset_full	.342
86	resnet_50_v1_spiking_l4	.339
87	resnet18_imagenet21kP	.338
88	resnet50-sup	.331
89	resnet_50_v1	.331
90	grcnn	.331
91	resnet101_imagenet_full	.329
92	mobilenet_v2_1_0_224	.326
93	xception	.323
94	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.320
95	cv_18_dagger_408_pretrained	.320
96	resnet_SIN_IN_FT_IN	.317
97	vonegrcnn_52e_full	.317
98	resnet50_imagenet_full	.316
99	BiT-S-R152x2	.315
100	antialias-resnet152	.312
101	inception_v1	.311
102	deit_small_imagenet_100_seed-0	.305
103	mobilenet_v2_1_0_128	.303
104	vonegrcnn_62e_nobn	.303
105	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.300
106	vonegrcnn_47e	.299
107	VOneCORnet-S	.298
108	densenet-201	.295
109	resnet50-SIN_IN	.293
110	custom_model_cv_18_dagger_408	.288
111	resnet50-SIN_IN_IN	.284
112	resnet34_imagenet_full	.277
113	vit_large_patch14_clip_336:laion2b_ft_in1k	.273
114	resnet50-barlow	.258
115	nasnet_mobile	.256
116	regnet_y_400mf	.251
117	efficientnet_b0_imagenet_full	.236
118	mobilenet_v2_0_75_160	.235
119	efficientnet_b2_imagenet_full	.229
120	densenet-121	.226
121	resnet18_imagenet_full	.215
122	mobilenet_v2_1_0_192	.214
123	mobilenet_v2_0_75_192	.211
124	mobilenet_v2_1_0_160	.211
125	vgg_19	.191
126	resnet50_robust_l2_eps1	.180
127	ReAlnet02	.180
128	ReAlnet02_cornet	.180
129	vgg_16	.166
130	shufflenet_v2_x1_0	.165
131	resnet50-vicregl0p9	.162
132	alexnet_training_seed_06	.162
133	yudixie_resnet18_imagenet1kpret_0_240719	.159
134	efficientnet_b1_imagenet_full	.156
135	ReAlnet07_cornet	.154
136	ReAlnet07	.154
137	mobilenet_v2_1_4_224	.144
138	mobilenet_v2_1-4_224_pytorch	.144
139	resnet-50-robust	.143
140	resnet50-SIN	.142
141	yudixie_resnet50_category_class_0_240908	.139
142	ReAlnet01_cornet	.133
143	ReAlnet01	.133
144	resnet-18_test_m	.132
145	alexnet_ks_torevert	.132
146	resnet50-vicreg	.129
147	ReAlnet05_cornet	.129
148	ReAlnet05	.129
149	ReAlnet08_cornet	.113
150	ReAlnet08	.113
151	yudixie_resnet18_object_class_0_240719	.113
152	ReAlnet03_cornet	.111
153	ReAlnet03	.111
154	resnet50_robust_l2_eps3	.110
155	imagenet_l2_3_0	.110
156	resnet50-vicregl0p75	.108
157	ReAlnet10_cornet	.101
158	ReAlnet10	.101
159	pnasnet_large_pytorch	.099
160	ReAlnet06	.096
161	ReAlnet06_cornet	.096
162	resnet50_eMMCR_Vanilla	.095
163	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.092
164	ReAlnet09_cornet	.092
165	ReAlnet09	.092
166	AlexNet_SIN	.089
167	ReAlnet04_cornet	.079
168	ReAlnet04	.079
169	yudixie_resnet18_category_class_0_240719	.077
170	mobilenet_v2_0_5_192	.077
171	alexnet_training_seed_03	.063
172	resnet50_imagenet_100_seed-0	.058
173	alexnet_training_seed_01	.052
174	alexnet_training_seed_02	.038
175	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.036
176	yudixie_resnet50_object_class_0_240908	.023
177	alexnet_training_seed_07	.023
178	alexnet_training_seed_05	.020
179	alexnet_training_seed_10	.018
180	alexnet_training_seed_09	.012
181	alexnet_training_seed_04	.007
182	yudixie_resnet50_rotation_reg_0_240908	.007
183	yudixie_resnet50_random_0_240908	.006
184	deit_small_imagenet_1_seed-0	.006
185	briaai_rmbg_1_4	.005
186	alexnet_training_seed_08	.005
187	resnet_50_v1_spiking_l3	.003
188	resnet50_imagenet_10_seed-0	.002
189	yudixie_resnet50_distance_rotation_0_240908	.002
190	yudixie_resnet18_random_0_240719	.001
191	yudixie_resnet50_distance_translation_0_240908	.000
192	yudixie_resnet50_distance_reg_0_240908	.000
193	yudixie_resnet18_rotation_reg_0_240719	.000
194	convnext_small_imagenet_1_seed-0	.002
195	yudixie_resnet18_translation_rotation_0_240719	.002
196	deit_small_imagenet_10_seed-0	.002
197	resnet50_imagenet_1_seed-0	.002
198	yudixie_resnet18_distance_reg_0_240719	.006
199	yudixie_resnet18_distance_rotation_0_240719	.007
200	yudixie_resnet50_distance_translation_rotation_0_240908	.008
201	yudixie_resnet18_translation_reg_0_240719	.009
202	yudixie_resnet50_translation_rotation_0_240908	.017
203	yudixie_resnet50_translation_reg_0_240908	.023
204	yudixie_resnet18_distance_translation_rotation_0_240719	.023
205	yudixie_resnet18_distance_translation_0_240719	.033
206	convnext_small_imagenet_10_seed-0	.034
207	artResNet18_1	.067
208	resnet50_primary_visual_cortex	.069
209	hmax	.142
210	TAU
211	densenet-169
212	SimVP
213	ConvLSTM
214	antialiased-rnext101_32x8d
215	convnext_base:clip_laiona_augreg_ft_in1k_384
216	mobilenet_v2_0_75_224
217	pnasnet_large
218	omnivore_swinB
219	BiT-S-R50x3
220	BiT-S-R152x4
221	BiT-S-R101x3
222	mobilenet_v2_0_5_224
223	MIM
224	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k
225	mobilenet_v2_1_3_224
226	PredRNN
227	voneresnet-50-robust
228	mobilevit_small

Benchmark bibtex

None

Ceiling

Not available

Data: tong.Coggan2024_behavior

Metric: ConditionWiseAccuracySimilarity