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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_base_fb_in1k	.707
4	convnext_large_imagenet_full_seed-0	.700
5	convnext_base_fb_in22k_ft_in1k	.689
6	vit_base_patch16_clip_224:openai_ft_in1k	.677
7	convnext_base_fb_in1k_gram_aligned_dinov3	.673
8	cvt_cvt-21-384-in1k_4_LucyV4	.659
9	convnext_xlarge:fb_in22k_ft_in1k	.636
10	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.635
11	focalnet_tiny_lrf_in1k	.628
12	cvt_cvt-21-224-in1k_4_LucyV4	.626
13	convnext_base_imagenet_full_seed-0	.619
14	convnext_tiny:in12k_ft_in1k	.613
15	vit_relpos_base_patch16_clsgap_224:sw_in1k	.611
16	convnext_large:fb_in22k_ft_in1k	.603
17	AdvProp_efficientnet-b7	.597
18	tv_efficientnet-b1	.595
19	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.591
20	resnet50-vitoimagevidnet8	.590
21	resnet50-VITO-8deg-cc	.590
22	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.588
23	resnet101_ecoset_full	.588
24	cvt_cvt-13-224-in1k_4_LucyV4	.586
25	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.575
26	effnetb1_272x240	.573
27	resnet152_ecoset_full	.571
28	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.566
29	AdvProp_efficientnet-b6	.558
30	omnivore_swinS	.555
31	resnext101_32x8d_wsl	.554
32	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.552
33	AT_efficientnet-b2	.552
34	AdvProp_efficientnet-b2	.552
35	efficientnet-b7	.551
36	ViT_L_32_imagenet1k	.542
37	resnet50_ewconplus_wzc	.542
38	resnet_101_v2	.541
39	convnext_small_imagenet_full_seed-0	.540
40	resnet50_ewconplus_noseed_2_323	.537
41	resnext101_32x48d_wsl	.536
42	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.535
43	resnext101_32x16d_wsl	.534
44	convnext_tiny_imagenet_full_seed-0	.529
45	vit_large_patch14_clip_224:openai_ft_in1k	.526
46	deit_large_imagenet_full_seed-0	.523
47	convnext_tiny_sup	.519
48	resnet50_st_wzc_seed3_2_323	.519
49	resnet_50_v2	.515
50	resnet50-moclr8deg	.515
51	resnet50_ewconplus_wzc_seed6_2_323	.507
52	vit_large_patch14_clip_224:laion2b_ft_in1k	.505
53	resnet50_ecoset_full	.504
54	cvt_cvt-13-384-in1k_4_LucyV4	.501
55	AdvProp_efficientnet-b8	.497
56	resnet50_st_wzc_seed4_2_323	.483
57	BiT-S-R50x1	.482
58	resnet_152_v2	.478
59	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.476
60	deit_base_imagenet_full_seed-0	.471
61	resnext101_32x32d_wsl	.469
62	resnet50_ewconplus_wzc_seed2_2__323	.469
63	resnet50_ewconplus_wzc_seed5_2__323	.467
64	resnet-152_v2_pytorch	.466
65	resnet50_st_wzc_seed7_2_323	.465
66	efficientnet_b0	.463
67	resnet50_st_wzc_seed6_2_323	.460
68	resnet152_imagenet_full	.459
69	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.457
70	resnet50_st_wzc_2	.454
71	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.453
72	resnet50_st_wzc_2_323	.452
73	resnet50_st_wzc_seed5_2_323	.449
74	AdvProp_efficientnet-b4	.448
75	deit_small_imagenet_full_seed-0	.448
76	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.446
77	convnext_femto_ols:d1_in1k	.434
78	inception_v3	.430
79	grcnn_109	.425
80	voneresnet-50	.421
81	densenet_201_pytorch	.412
82	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.411
83	yolos_tiny	.409
84	antialiased-r50	.409
85	resnet50_tutorial	.407
86	resnet50_ewconplus_wzc_seed4_2_323	.406
87	resnet50_st_wzc_noseed_2_323	.405
88	voneresnet-50-non_stochastic	.398
89	pnasnet_large_halfPrecision	.397
90	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.393
91	resnet_50_v1_spiking_l4a	.392
92	nasnet_large	.383
93	resnet_50_v1_spiking	.383
94	BiT-S-R101x1	.379
95	convnext_small_imagenet_100_seed-0	.374
96	inception_v4	.372
97	blt_vs	.372
98	Res2Net50_26w_4s	.371
99	resnet_152_v1	.371
100	inception_v3_pytorch	.360
101	yudixie_resnet50_imagenet1kpret_0_240908	.359
102	resnet18_ecoset_full	.356
103	resnet_101_v1	.351
104	resnet34_ecoset_full	.342
105	resnet_50_v1_spiking_l4	.339
106	resnet18_imagenet21kP	.338
107	predictive_coding_pc	.333
108	resnet_50_v1	.331
109	resnet50-sup	.331
110	grcnn	.331
111	resnet101_imagenet_full	.329
112	mobilenet_v2_1_0_224	.326
113	xception	.323
114	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.320
115	cv_18_dagger_408_pretrained	.320
116	resnet_SIN_IN_FT_IN	.317
117	vonegrcnn_52e_full	.317
118	resnet50_imagenet_full	.316
119	BiT-S-R152x2	.315
120	antialias-resnet152	.312
121	inception_v1	.311
122	deit_small_imagenet_100_seed-0	.305
123	mobilenet_v2_1_0_128	.303
124	vonegrcnn_62e_nobn	.303
125	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.300
126	vonegrcnn_47e	.299
127	VOneCORnet-S	.298
128	densenet-201	.295
129	resnet50-SIN_IN	.293
130	custom_model_cv_18_dagger_408	.288
131	resnet50-SIN_IN_IN	.284
132	resnet34_imagenet_full	.277
133	vit_large_patch14_clip_336:laion2b_ft_in1k	.273
134	ReAlnet03_ALL	.258
135	resnet50-barlow	.258
136	nasnet_mobile	.256
137	regnet_y_400mf	.251
138	ReAlnet06_ALL	.250
139	efficientnet_b0_imagenet_full	.236
140	mobilenet_v2_0_75_160	.235
141	efficientnet_b2_imagenet_full	.229
142	ReAlnet01_cornet_fov12	.229
143	ReAlnet01_ALL	.228
144	ReAlnet10_ALL	.226
145	densenet-121	.226
146	ReAlnet08_ALL	.219
147	ReAlnet07_ALL	.216
148	resnet18_imagenet_full	.215
149	mobilenet_v2_1_0_192	.214
150	mobilenet_v2_0_75_192	.211
151	mobilenet_v2_1_0_160	.211
152	ReAlnet09_ALL	.210
153	ReAlnet05_ALL	.207
154	ReAlnet02_ALL	.201
155	ReAlnet04_ALL	.198
156	vgg_19	.191
157	deepeisnn_ei_imagenet_resnet18	.186
158	resnet50_robust_l2_eps1	.180
159	ReAlnet02_cornet	.180
160	ReAlnet02	.180
161	alexnet_fov12	.170
162	vgg_16	.166
163	shufflenet_v2_x1_0	.165
164	ReAlnet01_cornet_fov16	.162
165	resnet50-vicregl0p9	.162
166	alexnet_training_seed_06	.162
167	yudixie_resnet18_imagenet1kpret_0_240719	.159
168	efficientnet_b1_imagenet_full	.156
169	ReAlnet07_cornet	.154
170	ReAlnet07	.154
171	AlexNet_SIN_fov12	.153
172	alexnet_fov16	.148
173	mobilenet_v2_1_4_224	.144
174	mobilenet_v2_1-4_224_pytorch	.144
175	resnet-50-robust	.143
176	resnet50-SIN	.142
177	yudixie_resnet50_category_class_0_240908	.139
178	ReAlnet01_cornet	.133
179	ReAlnet01	.133
180	resnet-18_test_m	.132
181	alexnet_ks_torevert	.132
182	alexnet	.132
183	resnet50-vicreg	.129
184	ReAlnet05_cornet	.129
185	ReAlnet05	.129
186	yudixie_wbh_object_class_scaling_0415_run_1	.123
187	yudixie_wbh_object_class_scaling_0415_run_3	.123
188	ReAlnet01_cornet_fov4	.122
189	ReAlnet08_cornet	.113
190	ReAlnet08	.113
191	yudixie_resnet18_object_class_0_240719	.113
192	ReAlnet03_cornet	.111
193	ReAlnet03	.111
194	resnet50_robust_l2_eps3	.110
195	imagenet_l2_3_0	.110
196	resnet50-vicregl0p75	.108
197	yudixie_wbh_object_class_scaling_0415_imagenet	.106
198	yudixie_wbh_object_class_scaling_0415_run_2	.103
199	ReAlnet10_cornet	.101
200	ReAlnet10	.101
201	pnasnet_large_pytorch	.099
202	ReAlnet06_cornet	.096
203	ReAlnet06	.096
204	resnet50_eMMCR_Vanilla	.095
205	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.092
206	ReAlnet09_cornet	.092
207	ReAlnet09	.092
208	AlexNet_SIN	.089
209	ReAlnet04_cornet	.079
210	ReAlnet04	.079
211	alexnet_fov4	.078
212	yudixie_resnet18_category_class_0_240719	.077
213	mobilenet_v2_0_5_192	.077
214	AlexNet_SIN_fov16	.077
215	alexnet_training_seed_01_fov4	.064
216	alexnet_training_seed_03	.063
217	yudixie_wbh_object_class_scaling_0415_run_0	.062
218	resnet50_imagenet_100_seed-0	.058
219	alexnet_training_seed_01	.052
220	deepeisnn_ei_cifar10_vgg19	.048
221	AlexNet_SIN_fov4	.044
222	compact_vgg19_IT	.043
223	alexnet_training_seed_02	.038
224	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.036
225	compact_cornets_V4	.035
226	yudixie_resnet50_object_class_0_240908	.023
227	alexnet_training_seed_07	.023
228	alexnet_training_seed_01_fov12	.022
229	compact_resnet50_IT	.021
230	alexnet_training_seed_05	.020
231	alexnet_training_seed_01_fov16	.019
232	alexnet_training_seed_10	.018
233	alexnet_training_seed_09	.012
234	compact_vgg19_V4	.009
235	alexnet_training_seed_04	.007
236	yudixie_resnet50_rotation_reg_0_240908	.007
237	deepeisnn_ei_cifar10_resnet18	.007
238	yudixie_resnet50_random_0_240908	.006
239	deit_small_imagenet_1_seed-0	.006
240	pr1_stl10_disentangled_alpha04	.006
241	compact_resnet50_robust_IT	.006
242	briaai_rmbg_1_4	.005
243	alexnet_training_seed_08	.005
244	compact_resnet50_V4	.005
245	compact_resnet50_robust_V4	.004
246	resnet18_fair	.003
247	resnet_50_v1_spiking_l3	.003
248	resnet50_imagenet_10_seed-0	.002
249	yudixie_resnet50_distance_rotation_0_240908	.002
250	yudixie_resnet18_random_0_240719	.001
251	yudixie_resnet50_distance_translation_0_240908	.000
252	yudixie_resnet50_distance_reg_0_240908	.000
253	compact_cornets_IT	.000
254	yudixie_resnet18_rotation_reg_0_240719	.000
255	convnext_small_imagenet_1_seed-0	.002
256	yudixie_resnet18_translation_rotation_0_240719	.002
257	deit_small_imagenet_10_seed-0	.002
258	resnet50_imagenet_1_seed-0	.002
259	aughost_fair_resnet18	.004
260	yudixie_resnet18_distance_reg_0_240719	.006
261	yudixie_resnet18_distance_rotation_0_240719	.007
262	yudixie_resnet50_distance_translation_rotation_0_240908	.008
263	yudixie_resnet18_translation_reg_0_240719	.009
264	yudixie_resnet50_translation_rotation_0_240908	.017
265	yudixie_resnet50_translation_reg_0_240908	.023
266	yudixie_resnet18_distance_translation_rotation_0_240719	.023
267	yudixie_resnet18_distance_translation_0_240719	.033
268	convnext_small_imagenet_10_seed-0	.034
269	artResNet18_1	.067
270	resnet50_primary_visual_cortex	.069
271	hmax	.142
272	deit3_base_patch16_224_fb_in22k_ft_in1k
273	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3
274	deit3_base_patch16_224_fb_in1k
275	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
276	resnet50_ewconplus_wzc_seed7_2_323
277	vit_base_patch16_dinov3-lvd1689m
278	vit_base_patch14_reg4_dinov2-lvd142m
279	vit_base_patch14_dinov2-lvd142m
280	mobilenet_v2_1_3_224
281	pnasnet_large
282	mobilenet_v2_0_75_224
283	mobilenet_v2_0_5_224
284	voneresnet-50-robust
285	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k
286	omnivore_swinB
287	convnext_base:clip_laiona_augreg_ft_in1k_384
288	densenet-169
289	BiT-S-R101x3
290	BiT-S-R152x4
291	BiT-S-R50x3
292	MIM
293	PredRNN
294	mobilevit_small
295	TAU
296	SimVP
297	ConvLSTM
298	antialiased-rnext101_32x8d

Benchmark bibtex

None

Ceiling

0.69.

Note that scores are relative to this ceiling.

Data: tong.Coggan2024_behavior

Metric: ConditionWiseAccuracySimilarity