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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	resnet50_ewconplus_wzc	.542
34	resnet_101_v2	.541
35	convnext_small_imagenet_full_seed-0	.540
36	resnext101_32x48d_wsl	.536
37	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.535
38	resnext101_32x16d_wsl	.534
39	convnext_tiny_imagenet_full_seed-0	.529
40	vit_large_patch14_clip_224:openai_ft_in1k	.526
41	deit_large_imagenet_full_seed-0	.523
42	convnext_tiny_sup	.519
43	resnet_50_v2	.515
44	resnet50-moclr8deg	.515
45	vit_large_patch14_clip_224:laion2b_ft_in1k	.505
46	resnet50_ecoset_full	.504
47	cvt_cvt-13-384-in1k_4_LucyV4	.501
48	AdvProp_efficientnet-b8	.497
49	BiT-S-R50x1	.482
50	resnet_152_v2	.478
51	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.476
52	deit_base_imagenet_full_seed-0	.471
53	resnext101_32x32d_wsl	.469
54	resnet-152_v2_pytorch	.466
55	efficientnet_b0	.463
56	resnet152_imagenet_full	.459
57	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.457
58	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.453
59	AdvProp_efficientnet-b4	.448
60	deit_small_imagenet_full_seed-0	.448
61	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.446
62	convnext_femto_ols:d1_in1k	.434
63	inception_v3	.430
64	grcnn_109	.425
65	voneresnet-50	.421
66	densenet_201_pytorch	.412
67	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.411
68	yolos_tiny	.409
69	antialiased-r50	.409
70	resnet50_tutorial	.407
71	voneresnet-50-non_stochastic	.398
72	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.393
73	resnet_50_v1_spiking_l4a	.392
74	nasnet_large	.383
75	resnet_50_v1_spiking	.383
76	BiT-S-R101x1	.379
77	convnext_small_imagenet_100_seed-0	.374
78	inception_v4	.372
79	blt_vs	.372
80	Res2Net50_26w_4s	.371
81	resnet_152_v1	.371
82	inception_v3_pytorch	.360
83	yudixie_resnet50_imagenet1kpret_0_240908	.359
84	resnet18_ecoset_full	.356
85	resnet_101_v1	.351
86	resnet34_ecoset_full	.342
87	resnet_50_v1_spiking_l4	.339
88	resnet18_imagenet21kP	.338
89	resnet_50_v1	.331
90	resnet50-sup	.331
91	grcnn	.331
92	resnet101_imagenet_full	.329
93	mobilenet_v2_1_0_224	.326
94	xception	.323
95	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.320
96	cv_18_dagger_408_pretrained	.320
97	resnet_SIN_IN_FT_IN	.317
98	vonegrcnn_52e_full	.317
99	resnet50_imagenet_full	.316
100	BiT-S-R152x2	.315
101	antialias-resnet152	.312
102	inception_v1	.311
103	deit_small_imagenet_100_seed-0	.305
104	mobilenet_v2_1_0_128	.303
105	vonegrcnn_62e_nobn	.303
106	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.300
107	vonegrcnn_47e	.299
108	VOneCORnet-S	.298
109	densenet-201	.295
110	resnet50-SIN_IN	.293
111	custom_model_cv_18_dagger_408	.288
112	resnet50-SIN_IN_IN	.284
113	resnet34_imagenet_full	.277
114	vit_large_patch14_clip_336:laion2b_ft_in1k	.273
115	ReAlnet03_ALL	.258
116	resnet50-barlow	.258
117	nasnet_mobile	.256
118	regnet_y_400mf	.251
119	ReAlnet06_ALL	.250
120	efficientnet_b0_imagenet_full	.236
121	mobilenet_v2_0_75_160	.235
122	efficientnet_b2_imagenet_full	.229
123	ReAlnet01_ALL	.228
124	ReAlnet10_ALL	.226
125	densenet-121	.226
126	ReAlnet08_ALL	.219
127	ReAlnet07_ALL	.216
128	resnet18_imagenet_full	.215
129	mobilenet_v2_1_0_192	.214
130	mobilenet_v2_0_75_192	.211
131	mobilenet_v2_1_0_160	.211
132	ReAlnet09_ALL	.210
133	ReAlnet05_ALL	.207
134	ReAlnet02_ALL	.201
135	ReAlnet04_ALL	.198
136	vgg_19	.191
137	resnet50_robust_l2_eps1	.180
138	ReAlnet02_cornet	.180
139	ReAlnet02	.180
140	vgg_16	.166
141	shufflenet_v2_x1_0	.165
142	resnet50-vicregl0p9	.162
143	alexnet_training_seed_06	.162
144	yudixie_resnet18_imagenet1kpret_0_240719	.159
145	efficientnet_b1_imagenet_full	.156
146	ReAlnet07	.154
147	ReAlnet07_cornet	.154
148	mobilenet_v2_1_4_224	.144
149	mobilenet_v2_1-4_224_pytorch	.144
150	resnet-50-robust	.143
151	resnet50-SIN	.142
152	yudixie_resnet50_category_class_0_240908	.139
153	ReAlnet01_cornet	.133
154	ReAlnet01	.133
155	resnet-18_test_m	.132
156	alexnet_ks_torevert	.132
157	resnet50-vicreg	.129
158	ReAlnet05	.129
159	ReAlnet05_cornet	.129
160	ReAlnet08	.113
161	ReAlnet08_cornet	.113
162	yudixie_resnet18_object_class_0_240719	.113
163	ReAlnet03	.111
164	ReAlnet03_cornet	.111
165	imagenet_l2_3_0	.110
166	resnet50_robust_l2_eps3	.110
167	resnet50-vicregl0p75	.108
168	ReAlnet10	.101
169	ReAlnet10_cornet	.101
170	pnasnet_large_pytorch	.099
171	ReAlnet06	.096
172	ReAlnet06_cornet	.096
173	resnet50_eMMCR_Vanilla	.095
174	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.092
175	ReAlnet09	.092
176	ReAlnet09_cornet	.092
177	AlexNet_SIN	.089
178	ReAlnet04_cornet	.079
179	ReAlnet04	.079
180	yudixie_resnet18_category_class_0_240719	.077
181	mobilenet_v2_0_5_192	.077
182	alexnet_training_seed_03	.063
183	resnet50_imagenet_100_seed-0	.058
184	alexnet_training_seed_01	.052
185	compact_vgg19_IT	.043
186	alexnet_training_seed_02	.038
187	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.036
188	compact_cornets_V4	.035
189	yudixie_resnet50_object_class_0_240908	.023
190	alexnet_training_seed_07	.023
191	compact_resnet50_IT	.021
192	alexnet_training_seed_05	.020
193	alexnet_training_seed_10	.018
194	alexnet_training_seed_09	.012
195	compact_vgg19_V4	.009
196	alexnet_training_seed_04	.007
197	yudixie_resnet50_rotation_reg_0_240908	.007
198	yudixie_resnet50_random_0_240908	.006
199	deit_small_imagenet_1_seed-0	.006
200	compact_resnet50_robust_IT	.006
201	briaai_rmbg_1_4	.005
202	alexnet_training_seed_08	.005
203	compact_resnet50_V4	.005
204	compact_resnet50_robust_V4	.004
205	resnet_50_v1_spiking_l3	.003
206	resnet50_imagenet_10_seed-0	.002
207	yudixie_resnet50_distance_rotation_0_240908	.002
208	yudixie_resnet18_random_0_240719	.001
209	yudixie_resnet50_distance_translation_0_240908	.000
210	yudixie_resnet50_distance_reg_0_240908	.000
211	compact_cornets_IT	.000
212	yudixie_resnet18_rotation_reg_0_240719	.000
213	convnext_small_imagenet_1_seed-0	.002
214	yudixie_resnet18_translation_rotation_0_240719	.002
215	deit_small_imagenet_10_seed-0	.002
216	resnet50_imagenet_1_seed-0	.002
217	yudixie_resnet18_distance_reg_0_240719	.006
218	yudixie_resnet18_distance_rotation_0_240719	.007
219	yudixie_resnet50_distance_translation_rotation_0_240908	.008
220	yudixie_resnet18_translation_reg_0_240719	.009
221	yudixie_resnet50_translation_rotation_0_240908	.017
222	yudixie_resnet50_translation_reg_0_240908	.023
223	yudixie_resnet18_distance_translation_rotation_0_240719	.023
224	yudixie_resnet18_distance_translation_0_240719	.033
225	convnext_small_imagenet_10_seed-0	.034
226	artResNet18_1	.067
227	resnet50_primary_visual_cortex	.069
228	hmax	.142
229	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k
230	mobilenet_v2_0_75_224
231	antialiased-rnext101_32x8d
232	ConvLSTM
233	SimVP
234	TAU
235	mobilevit_small
236	PredRNN
237	MIM
238	mobilenet_v2_0_5_224
239	omnivore_swinB
240	pnasnet_large
241	voneresnet-50-robust
242	mobilenet_v2_1_3_224
243	BiT-S-R50x3
244	BiT-S-R152x4
245	BiT-S-R101x3
246	densenet-169
247	convnext_base:clip_laiona_augreg_ft_in1k_384

Benchmark bibtex

None

Ceiling

Not available

Data: tong.Coggan2024_behavior

Metric: ConditionWiseAccuracySimilarity