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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	AdvProp_efficientnet-b2	.552
30	AT_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	resnet_50_v1	.331
89	resnet50-sup	.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	ReAlnet03_ALL	.258
115	resnet50-barlow	.258
116	nasnet_mobile	.256
117	regnet_y_400mf	.251
118	ReAlnet06_ALL	.250
119	efficientnet_b0_imagenet_full	.236
120	mobilenet_v2_0_75_160	.235
121	efficientnet_b2_imagenet_full	.229
122	ReAlnet01_ALL	.228
123	ReAlnet10_ALL	.226
124	densenet-121	.226
125	ReAlnet08_ALL	.219
126	ReAlnet07_ALL	.216
127	resnet18_imagenet_full	.215
128	mobilenet_v2_1_0_192	.214
129	mobilenet_v2_0_75_192	.211
130	mobilenet_v2_1_0_160	.211
131	ReAlnet09_ALL	.210
132	ReAlnet05_ALL	.207
133	ReAlnet02_ALL	.201
134	ReAlnet04_ALL	.198
135	vgg_19	.191
136	resnet50_robust_l2_eps1	.180
137	ReAlnet02_cornet	.180
138	ReAlnet02	.180
139	vgg_16	.166
140	shufflenet_v2_x1_0	.165
141	resnet50-vicregl0p9	.162
142	alexnet_training_seed_06	.162
143	yudixie_resnet18_imagenet1kpret_0_240719	.159
144	efficientnet_b1_imagenet_full	.156
145	ReAlnet07	.154
146	ReAlnet07_cornet	.154
147	mobilenet_v2_1_4_224	.144
148	mobilenet_v2_1-4_224_pytorch	.144
149	resnet-50-robust	.143
150	resnet50-SIN	.142
151	yudixie_resnet50_category_class_0_240908	.139
152	ReAlnet01_cornet	.133
153	ReAlnet01	.133
154	resnet-18_test_m	.132
155	alexnet_ks_torevert	.132
156	resnet50-vicreg	.129
157	ReAlnet05	.129
158	ReAlnet05_cornet	.129
159	ReAlnet08	.113
160	ReAlnet08_cornet	.113
161	yudixie_resnet18_object_class_0_240719	.113
162	ReAlnet03	.111
163	ReAlnet03_cornet	.111
164	imagenet_l2_3_0	.110
165	resnet50_robust_l2_eps3	.110
166	resnet50-vicregl0p75	.108
167	ReAlnet10	.101
168	ReAlnet10_cornet	.101
169	pnasnet_large_pytorch	.099
170	ReAlnet06	.096
171	ReAlnet06_cornet	.096
172	resnet50_eMMCR_Vanilla	.095
173	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.092
174	ReAlnet09	.092
175	ReAlnet09_cornet	.092
176	AlexNet_SIN	.089
177	ReAlnet04_cornet	.079
178	ReAlnet04	.079
179	yudixie_resnet18_category_class_0_240719	.077
180	mobilenet_v2_0_5_192	.077
181	alexnet_training_seed_03	.063
182	resnet50_imagenet_100_seed-0	.058
183	alexnet_training_seed_01	.052
184	alexnet_training_seed_02	.038
185	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.036
186	yudixie_resnet50_object_class_0_240908	.023
187	alexnet_training_seed_07	.023
188	alexnet_training_seed_05	.020
189	alexnet_training_seed_10	.018
190	alexnet_training_seed_09	.012
191	alexnet_training_seed_04	.007
192	yudixie_resnet50_rotation_reg_0_240908	.007
193	yudixie_resnet50_random_0_240908	.006
194	deit_small_imagenet_1_seed-0	.006
195	briaai_rmbg_1_4	.005
196	alexnet_training_seed_08	.005
197	resnet_50_v1_spiking_l3	.003
198	resnet50_imagenet_10_seed-0	.002
199	yudixie_resnet50_distance_rotation_0_240908	.002
200	yudixie_resnet18_random_0_240719	.001
201	yudixie_resnet50_distance_translation_0_240908	.000
202	yudixie_resnet50_distance_reg_0_240908	.000
203	yudixie_resnet18_rotation_reg_0_240719	.000
204	convnext_small_imagenet_1_seed-0	.002
205	yudixie_resnet18_translation_rotation_0_240719	.002
206	deit_small_imagenet_10_seed-0	.002
207	resnet50_imagenet_1_seed-0	.002
208	yudixie_resnet18_distance_reg_0_240719	.006
209	yudixie_resnet18_distance_rotation_0_240719	.007
210	yudixie_resnet50_distance_translation_rotation_0_240908	.008
211	yudixie_resnet18_translation_reg_0_240719	.009
212	yudixie_resnet50_translation_rotation_0_240908	.017
213	yudixie_resnet50_translation_reg_0_240908	.023
214	yudixie_resnet18_distance_translation_rotation_0_240719	.023
215	yudixie_resnet18_distance_translation_0_240719	.033
216	convnext_small_imagenet_10_seed-0	.034
217	artResNet18_1	.067
218	resnet50_primary_visual_cortex	.069
219	hmax	.142
220	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k
221	mobilenet_v2_0_75_224
222	antialiased-rnext101_32x8d
223	ConvLSTM
224	SimVP
225	TAU
226	mobilevit_small
227	PredRNN
228	MIM
229	mobilenet_v2_0_5_224
230	omnivore_swinB
231	pnasnet_large
232	voneresnet-50-robust
233	mobilenet_v2_1_3_224
234	BiT-S-R50x3
235	BiT-S-R152x4
236	BiT-S-R101x3
237	densenet-169
238	convnext_base:clip_laiona_augreg_ft_in1k_384

Benchmark bibtex

None

Ceiling

Not available

Data: tong.Coggan2024_behavior

Metric: ConditionWiseAccuracySimilarity