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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	seresnext50_32x4d	.610
17	convnext_large:fb_in22k_ft_in1k	.603
18	AdvProp_efficientnet-b7	.597
19	tv_efficientnet-b1	.595
20	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.591
21	resnet50-vitoimagevidnet8	.590
22	resnet50-VITO-8deg-cc	.590
23	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.588
24	resnet101_ecoset_full	.588
25	cvt_cvt-13-224-in1k_4_LucyV4	.586
26	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.575
27	effnetb1_272x240	.573
28	resnet152_ecoset_full	.571
29	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.566
30	regnety_032	.565
31	AdvProp_efficientnet-b6	.558
32	omnivore_swinS	.555
33	resnext101_32x8d_wsl	.554
34	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.552
35	AT_efficientnet-b2	.552
36	AdvProp_efficientnet-b2	.552
37	efficientnet-b7	.551
38	ViT_L_32_imagenet1k	.542
39	resnet50_ewconplus_wzc	.542
40	resnet_101_v2	.541
41	convnext_small_imagenet_full_seed-0	.540
42	resnext101_32x48d_wsl	.536
43	dinov2_vitl14_lc	.535
44	dinov2_vitg14_reg_lc	.535
45	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.535
46	resnext101_32x16d_wsl	.534
47	convnext_tiny_imagenet_full_seed-0	.529
48	dinov2_vitg14_lc	.526
49	vit_large_patch14_clip_224:openai_ft_in1k	.526
50	deit_large_imagenet_full_seed-0	.523
51	dinov2_vitl14_reg_lc	.520
52	convnext_tiny_sup	.519
53	resnet50_st_wzc_seed3_2_323	.519
54	resnet_50_v2	.515
55	resnet50-moclr8deg	.515
56	resnet50_ewconplus_wzc_seed6_2_323	.507
57	vit_large_patch14_clip_224:laion2b_ft_in1k	.505
58	resnet50_ecoset_full	.504
59	cvt_cvt-13-384-in1k_4_LucyV4	.501
60	AdvProp_efficientnet-b8	.497
61	resnet50_hvs_wzc	.484
62	BiT-S-R50x1	.482
63	resnet_152_v2	.478
64	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.476
65	deit_base_imagenet_full_seed-0	.471
66	resnext101_32x32d_wsl	.469
67	resnet50_ewconplus_wzc_seed2_2__323	.469
68	resnet50_ewconplus_wzc_seed5_2__323	.467
69	resnet-152_v2_pytorch	.466
70	resnet50_st_wzc_seed7_2_323	.465
71	efficientnet_b0	.463
72	resnet50_st_wzc_seed6_2_323	.460
73	resnet152_imagenet_full	.459
74	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.457
75	resnet50_st_wzc_2	.454
76	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.453
77	AdvProp_efficientnet-b4	.448
78	deit_small_imagenet_full_seed-0	.448
79	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.446
80	convnext_femto_ols:d1_in1k	.434
81	inception_v3	.430
82	grcnn_109	.425
83	voneresnet-50	.421
84	densenet_201_pytorch	.412
85	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.411
86	yolos_tiny	.409
87	antialiased-r50	.409
88	resnet50_tutorial	.407
89	voneresnet-50-non_stochastic	.398
90	pnasnet_large_halfPrecision	.397
91	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.393
92	resnet_50_v1_spiking_l4a	.392
93	nasnet_large	.383
94	resnet_50_v1_spiking	.383
95	BiT-S-R101x1	.379
96	convnext_small_imagenet_100_seed-0	.374
97	inception_v4	.372
98	blt_vs	.372
99	Res2Net50_26w_4s	.371
100	resnet_152_v1	.371
101	inception_v3_pytorch	.360
102	yudixie_resnet50_imagenet1kpret_0_240908	.359
103	resnet18_ecoset_full	.356
104	resnet_101_v1	.351
105	resnet34_ecoset_full	.342
106	resnet_50_v1_spiking_l4	.339
107	resnet18_imagenet21kP	.338
108	predictive_coding_pc	.333
109	resnet_50_v1	.331
110	resnet50-sup	.331
111	grcnn	.331
112	resnet101_imagenet_full	.329
113	mobilenet_v2_1_0_224	.326
114	xception	.323
115	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.320
116	cv_18_dagger_408_pretrained	.320
117	resnet_SIN_IN_FT_IN	.317
118	vonegrcnn_52e_full	.317
119	resnet50_imagenet_full	.316
120	BiT-S-R152x2	.315
121	antialias-resnet152	.312
122	inception_v1	.311
123	deit_small_imagenet_100_seed-0	.305
124	mobilenet_v2_1_0_128	.303
125	vonegrcnn_62e_nobn	.303
126	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.300
127	vonegrcnn_47e	.299
128	VOneCORnet-S	.298
129	densenet-201	.295
130	resnet50-SIN_IN	.293
131	eicircuit_resnet18_bn_20260919	.288
132	custom_model_cv_18_dagger_408	.288
133	resnet50-SIN_IN_IN	.284
134	resnet34_imagenet_full	.277
135	vit_large_patch14_clip_336:laion2b_ft_in1k	.273
136	dinov2_vitl14_lc_res336	.261
137	ReAlnet03_ALL	.258
138	resnet50-barlow	.258
139	nasnet_mobile	.256
140	regnet_y_400mf	.251
141	ReAlnet06_ALL	.250
142	efficientnet_b0_imagenet_full	.236
143	mobilenet_v2_0_75_160	.235
144	efficientnet_b2_imagenet_full	.229
145	ReAlnet01_cornet_fov12	.229
146	ReAlnet01_ALL	.228
147	ReAlnet10_ALL	.226
148	densenet-121	.226
149	ReAlnet08_ALL	.219
150	ReAlnet07_ALL	.216
151	resnet18_imagenet_full	.215
152	mobilenet_v2_1_0_192	.214
153	mobilenet_v2_0_75_192	.211
154	mobilenet_v2_1_0_160	.211
155	ReAlnet09_ALL	.210
156	ReAlnet05_ALL	.207
157	ReAlnet02_ALL	.201
158	ReAlnet04_ALL	.198
159	vgg_19	.191
160	deepeisnn_ei_imagenet_resnet18	.186
161	resnet50_robust_l2_eps1	.180
162	ReAlnet02_cornet	.180
163	ReAlnet02	.180
164	alexnet_fov12	.170
165	vgg_16	.166
166	shufflenet_v2_x1_0	.165
167	ReAlnet01_cornet_fov16	.162
168	resnet50-vicregl0p9	.162
169	alexnet_training_seed_06	.162
170	yudixie_resnet18_imagenet1kpret_0_240719	.159
171	efficientnet_b1_imagenet_full	.156
172	ReAlnet07_cornet	.154
173	ReAlnet07	.154
174	AlexNet_SIN_fov12	.153
175	alexnet_fov16	.148
176	mobilenet_v2_1_4_224	.144
177	mobilenet_v2_1-4_224_pytorch	.144
178	resnet-50-robust	.143
179	resnet50-SIN	.142
180	yudixie_resnet50_category_class_0_240908	.139
181	ReAlnet01_cornet	.133
182	ReAlnet01	.133
183	resnet-18_test_m	.132
184	alexnet_ks_torevert	.132
185	alexnet	.132
186	resnet50-vicreg	.129
187	ReAlnet05_cornet	.129
188	ReAlnet05	.129
189	yudixie_wbh_object_class_scaling_0415_run_1	.123
190	yudixie_wbh_object_class_scaling_0415_run_3	.123
191	ReAlnet01_cornet_fov4	.122
192	ReAlnet08_cornet	.113
193	ReAlnet08	.113
194	yudixie_resnet18_object_class_0_240719	.113
195	ReAlnet03_cornet	.111
196	ReAlnet03	.111
197	resnet50_robust_l2_eps3	.110
198	imagenet_l2_3_0	.110
199	vonealexnet	.109
200	resnet50-vicregl0p75	.108
201	yudixie_wbh_object_class_scaling_0415_imagenet	.106
202	yudixie_wbh_object_class_scaling_0415_run_2	.103
203	ReAlnet10_cornet	.101
204	ReAlnet10	.101
205	pnasnet_large_pytorch	.099
206	ReAlnet06_cornet	.096
207	ReAlnet06	.096
208	resnet50_eMMCR_Vanilla	.095
209	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.092
210	ReAlnet09_cornet	.092
211	ReAlnet09	.092
212	gabor_filter_entropy_4x4_v2_forcedCosine	.090
213	AlexNet_SIN	.089
214	ReAlnet04_cornet	.079
215	ReAlnet04	.079
216	alexnet_fov4	.078
217	yudixie_resnet18_category_class_0_240719	.077
218	mobilenet_v2_0_5_192	.077
219	AlexNet_SIN_fov16	.077
220	gabor_filter_entropy_4x4	.072
221	alexnet_training_seed_01_fov4	.064
222	alexnet_training_seed_03	.063
223	yudixie_wbh_object_class_scaling_0415_run_0	.062
224	resnet50_imagenet_100_seed-0	.058
225	gabor_filter_entropy_4x4_v2	.054
226	alexnet_training_seed_01	.052
227	deepeisnn_ei_cifar10_vgg19	.048
228	AlexNet_SIN_fov4	.044
229	compact_vgg19_IT	.043
230	alexnet_training_seed_02	.038
231	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.036
232	compact_cornets_V4	.035
233	yudixie_resnet50_object_class_0_240908	.023
234	alexnet_training_seed_07	.023
235	alexnet_training_seed_01_fov12	.022
236	compact_resnet50_IT	.021
237	alexnet_training_seed_05	.020
238	persistence_memory	.020
239	alexnet_training_seed_01_fov16	.019
240	alexnet_training_seed_10	.018
241	alexnet_training_seed_09	.012
242	compact_vgg19_V4	.009
243	alexnet_training_seed_04	.007
244	yudixie_resnet50_rotation_reg_0_240908	.007
245	deepeisnn_ei_cifar10_resnet18	.007
246	yudixie_resnet50_random_0_240908	.006
247	deit_small_imagenet_1_seed-0	.006
248	pr1_stl10_disentangled_alpha04	.006
249	compact_resnet50_robust_IT	.006
250	briaai_rmbg_1_4	.005
251	alexnet_training_seed_08	.005
252	compact_resnet50_V4	.005
253	compact_resnet50_robust_V4	.004
254	resnet18_fair	.003
255	resnet_50_v1_spiking_l3	.003
256	resnet50_imagenet_10_seed-0	.002
257	yudixie_resnet50_distance_rotation_0_240908	.002
258	yudixie_resnet18_random_0_240719	.001
259	yudixie_resnet50_distance_translation_0_240908	.000
260	yudixie_resnet50_distance_reg_0_240908	.000
261	gabor_filter_mean_abs_4x4_v2	.000
262	compact_cornets_IT	.000
263	yudixie_resnet18_rotation_reg_0_240719	.000
264	convnext_small_imagenet_1_seed-0	.002
265	yudixie_resnet18_translation_rotation_0_240719	.002
266	deit_small_imagenet_10_seed-0	.002
267	resnet50_imagenet_1_seed-0	.002
268	yudixie_resnet18_distance_reg_0_240719	.006
269	yudixie_resnet18_distance_rotation_0_240719	.007
270	yudixie_resnet50_distance_translation_rotation_0_240908	.008
271	yudixie_resnet18_translation_reg_0_240719	.009
272	yudixie_resnet50_translation_rotation_0_240908	.017
273	persistence_mem	.017
274	yudixie_resnet50_translation_reg_0_240908	.023
275	yudixie_resnet18_distance_translation_rotation_0_240719	.023
276	yudixie_resnet18_distance_translation_0_240719	.033
277	convnext_small_imagenet_10_seed-0	.034
278	artResNet18_1	.067
279	resnet50_primary_visual_cortex	.069
280	hmax	.142
281	vit_huge_clip336_laion
282	convnext_xxlarge_clip
283	vit_large_clip336_openai
284	dinov2_vitl14_reg_lc_featread
285	eva02_large_in22k
286	convnext_large_in22k_supervised
287	convnext_large_clip_laion2b_finelayers
288	deit3_base_patch16_224_fb_in22k_ft_in1k
289	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3
290	deit3_base_patch16_224_fb_in1k
291	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3
292	vit_base_patch16_dinov3-lvd1689m
293	vit_base_patch14_reg4_dinov2-lvd142m
294	vit_base_patch14_dinov2-lvd142m
295	mobilenet_v2_1_3_224
296	pnasnet_large
297	mobilenet_v2_0_75_224
298	mobilenet_v2_0_5_224
299	voneresnet-50-robust
300	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k
301	omnivore_swinB
302	convnext_base:clip_laiona_augreg_ft_in1k_384
303	densenet-169
304	BiT-S-R101x3
305	BiT-S-R152x4
306	BiT-S-R50x3
307	MIM
308	PredRNN
309	mobilevit_small
310	TAU
311	SimVP
312	ConvLSTM
313	antialiased-rnext101_32x8d

Benchmark bibtex

None

Ceiling

0.69.

Note that scores are relative to this ceiling.

Data: tong.Coggan2024_behavior

Metric: ConditionWiseAccuracySimilarity