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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("SanghaviJozwik2020.IT-pls")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet50_robust_l2_eps3	.503
2	eBarlow_lmda_02_1000ep	.500
3	AT_efficientnet-b7	.490
4	resnet50-vicregl0p9	.487
5	resnet-18-LC_w_sh_100_iter_conv_init_m	.486
6	resnet50_robust_l2_eps1	.486
7	resnet-18-LC_w_sh_10_iter_m	.485
8	voneresnet-50-robust	.485
9	barlow-twins-resnet50	.484
10	resnet-18-LC_w_sh_100_iter_m	.483
11	resnet50-barlow	.482
12	resnet-50-robust	.482
13	resnet-50-pytorch	.482
14	resnet50-vicreg	.482
15	resnet-18-LC_w_sh_1_iter_conv_init_m	.480
16	AdvProp_efficientnet-b6	.476
17	custom_model_cv_18_dagger_408	.476
18	AdvProp_efficientnet-b7	.475
19	resnet-18-LC_d_w_sh_1x1_conv_init_m	.475
20	resnet-18-LC_w_sh_10_iter_conv_init_m	.475
21	alexnet_robust_correct	.473
22	convnext_tiny_imagenet_full_seed-0	.473
23	resnet50-vicregl0p75	.472
24	convnext_small_imagenet_full_seed-0	.471
25	AdvProp_efficientnet-b8	.471
26	resnet50-simclr-vissl	.470
27	0.5x_resnet-18_LC_w_sh_1_iter	.470
28	resnet50_ewconplus_wzc_2_323	.469
29	AT_efficientnet-b4	.467
30	resnet50_ewconplus_wzc_seed3_2_323	.466
31	0.5x_resnet-18_LC_w_sh_10_iter	.466
32	AT_efficientnet-b2	.466
33	resnet50_ewconplus_noseed_2_323	.466
34	resnet50_ewconplus_wzc_seed5_2__323	.465
35	resnet50_ewconplus_wzc_seed6_2_323	.464
36	AdvProp_efficientnet-b4	.463
37	vonegrcnn_62e_nobn	.463
38	vonegrcnn_52e_full	.463
39	convnext_base_imagenet_full_seed-0	.463
40	resnet50_ewconplus_wzc_seed2_2__323	.463
41	mobilenet_v2_0.5_160	.462
42	voneresnet-50	.462
43	ReAlnet01_cornet_fov12	.461
44	resnet50_random_linf8_perturb	.461
45	resnet50_ewconplus_wzc_seed4_2_323	.461
46	mobilenet_v2_0.75_128	.460
47	convnext_large_imagenet_full_seed-0	.460
48	mobilenet_v2_1.0_96	.460
49	konkle_alexnetgn_ipcl_ref01_primary_model	.459
50	alexnet_l2_3_robust	.459
51	mobilenet_v2_0.75_96	.459
52	resnet50_random_l2_perturb	.458
53	resnet50_l2_3_robust	.458
54	AdvProp_efficientnet-b2	.458
55	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.458
56	resnet50_ewconplus_wzc_seed7_2_323	.457
57	mobilenet_v2_0.5_96	.457
58	resnet-50_v1-tf	.456
59	vit_relpos_base_patch16_clsgap_224:sw_in1k	.456
60	resnet-152_v1-tf	.455
61	tv_efficientnet-b1	.455
62	imagenet_l2_10_0	.455
63	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.455
64	resnet18-instance_recognition	.455
65	ReAlnet01_cornet_fov16	.455
66	resnet50_st_wzc_noseed_2_323	.454
67	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.454
68	convnext_xlarge:fb_in22k_ft_in1k	.454
69	mobilenet_v1_1.0_128	.453
70	resnet50-VITO-8deg-cc	.453
71	resnet-18-LC_w_sh_1_iter_m	.453
72	mobilenet_v2_1.0_128-tf	.453
73	vision_transformer_vit_large_patch16_224	.452
74	mobilenet_v2_0.5_128	.452
75	AdvProp_efficientnet-b0	.451
76	resnet50-vitoimagevidnet8	.451
77	resnet50_imagenet_full	.451
78	Res2Net50_26w_4s	.450
79	vonegrcnn_47e	.450
80	effnetv2m_custom384	.450
81	mobilenet_v2_0.35_160	.450
82	resnet50_ecoset_full	.450
83	resnet50_st_wzc_seed6_2_323	.450
84	mobilenet_v2_1_0_128	.449
85	resnet50-moclr8deg	.449
86	resnet50_linf_8_robust	.449
87	imagenet_l2_3_0	.448
88	resnet50_st_wzc_2_323	.448
89	resnet-101_v1-tf	.448
90	0.5x_resnet-18_LC_w_sh_100_iter	.447
91	ReAlnet08_cornet	.447
92	cvt_cvt-13-224-in1k_4_LucyV4	.447
93	deit_base_imagenet_full_seed-0	.447
94	mobilenet_v2_0.35_96	.446
95	mobilenet_v2_0.75_160-tf	.446
96	resnet50_ewconplus_wzc	.446
97	cv_18_dagger_408_pretrained	.446
98	ReAlnet10_cornet	.446
99	vonegrcnn_47e	.445
100	resnet50_st_wzc_seed5_2_323	.445
101	ReAlnet03_cornet	.445
102	resnet101	.445
103	resnet50	.445
104	voneresnet-50-non_stochastic	.445
105	mobilenet_v2_0_75_160	.444
106	resnet50_st_wzc_seed4_2_323	.444
107	ReAlnet06_cornet	.443
108	ReAlnet07_cornet	.443
109	resnet50_imagenet_100_seed-0	.443
110	nasnet_mobile	.443
111	ReAlnet02_cornet	.443
112	mobilenet_v2_0.5_192-tf	.443
113	resnet50_linf_4_robust	.442
114	yudixie_resnet50_imagenet1kpret_0_240312	.442
115	resnet_50_v1_spiking_l4	.442
116	resnet_50_v1_spiking_l4a	.442
117	resnet50_tutorial	.442
118	yudixie_resnet50_imagenet1kpret_0_240908	.442
119	resnet50-SIN_IN_IN	.442
120	efficientnet_b0_imagenet_full	.442
121	ReAlnet04_cornet	.441
122	mobilenet_v2_0.75_192-tf	.441
123	ReAlnet09_cornet	.441
124	efficientnet_b1_imagenet_full	.441
125	omnivore_swinT	.441
126	ViT_L_32_imagenet1k	.441
127	mobilenet_v1_1.0_160	.440
128	ReAlnet01_cornet	.440
129	mobilenet_v2_1_4_224	.440
130	resnet-18-LC_1st_conv_m	.440
131	mobilenet_v2_1-4_224_pytorch	.439
132	ReAlnet05_cornet	.439
133	resnet-18-LC_m	.438
134	efficientnet-b7	.438
135	resnet50_st_wzc_seed3_2_323	.438
136	mobilenet_v2_0.35_128	.437
137	resnet50_st_wzc_seed7_2_323	.437
138	resnet152_imagenet_full	.437
139	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.436
140	resnet50-SIN_IN	.436
141	mobilenet_v2_1.0_160-tf	.435
142	mobilenet_v2_1.3_224-tf	.435
143	antialias-resnet152	.435
144	convnext_tiny:in12k_ft_in1k	.435
145	regnet_y_400mf	.435
146	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.434
147	resnext101_32x8d_wsl	.434
148	mobilenet_v2_0.35_192	.434
149	mobilenet_v2_0.5_224-tf	.434
150	resnet101_ecoset_full	.434
151	cvt_cvt-21-224-in1k_4_LucyV4	.433
152	resnet-50_v2-tf	.433
153	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.433
154	omnivore_swinB	.433
155	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.433
156	resnet-101_v2-tf	.433
157	mobilenet_v2_1_0_160	.433
158	BiT-S-R152x4	.433
159	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.432
160	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.432
161	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.432
162	mobilenet_v2_0.75_224-tf	.432
163	mobilenet_v1_0.75_160	.431
164	mobilenet_v2_0_5_192	.431
165	mobilenet_v2_1.4_224-tf	.431
166	efficientnet_b2_imagenet_full	.431
167	CORnet-S	.431
168	ViT-B/32	.430
169	effnetb1_272x240	.430
170	mobilenet_v2_1.0_192-tf	.430
171	grcnn	.430
172	efficientnet_b0	.430
173	mobilenet_v2_0_75_192	.429
174	focalnet_tiny_lrf_in1k	.429
175	cvt_cvt-13-384-in1k_4_LucyV4	.429
176	alexnet_linf_8_robust	.429
177	CLIP_ViT-B_32	.429
178	inception_v1-tf	.429
179	ReAlnet03_ALL	.429
180	ReAlnet07_ALL	.428
181	ReAlnet10_ALL	.428
182	ReAlnet01_ALL	.428
183	BiT-M-R152x4	.428
184	resnet152_ecoset_full	.428
185	ReAlnet02_ALL	.428
186	ReAlnet08_ALL	.427
187	cvt_cvt-21-384-in1k_4_LucyV4	.427
188	omnivore_swinS	.427
189	resnet34_ecoset_full	.427
190	FrankRobWobv0	.427
191	mobilenet_v1_0.5_192	.427
192	ReAlnet04_ALL	.426
193	0.5x_resnet-18_LC	.426
194	antialiased-r50	.426
195	ReAlnet06_ALL	.426
196	mobilenet_v2_0.35_224	.426
197	convnext_base:clip_laiona_augreg_ft_in1k_384	.426
198	ReAlnet09_ALL	.426
199	ReAlnet05_ALL	.426
200	antialiased-rnext101_32x8d	.425
201	densenet-201-keras	.425
202	densenet-201	.425
203	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.424
204	mobilenet_v2_1_0_224	.424
205	mobilenet_v1_0.25_160	.424
206	0.5x_resnet-18	.424
207	resnet-18-LC_conv_init_m	.423
208	mobilenet_v2_1.0_224-tf	.423
209	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.423
210	mobilenet_v2_1_0_192	.423
211	shufflenet_v2_x1_0	.423
212	deit_large_imagenet_full_seed-0	.422
213	convnext_large:fb_in22k_ft_in1k	.422
214	densenet-169	.421
215	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.421
216	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.420
217	deit3_base_patch16_224_fb_in1k	.420
218	resnet50_st_wzc_2	.420
219	mobilenet_v2_0_75_224	.419
220	resnet101_imagenet_full	.419
221	grcnn_robust_v1	.419
222	mobilenet_v1_0.75_192	.419
223	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.419
224	grcnn_109	.418
225	mobilenet_v1_1.0_192	.418
226	nasnet_mobile-tf	.417
227	deit_small_imagenet_full_seed-0	.416
228	resnet50-SIN	.416
229	nasnet_large-tf	.416
230	yudixie_resnet18_imagenet1kpret_0_240719	.416
231	yudixie_wbh_object_class_scaling_0415_imagenet	.416
232	mobilenet_v1_0.5_128	.415
233	densenet-169-keras	.414
234	mobilenet_v1_0.25_192	.414
235	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.414
236	SWSL_resnet50	.414
237	mobilenet_v1_0.75_224	.414
238	resnet_50_v1_spiking	.413
239	resnet50-sup	.413
240	resnet_50_v1	.413
241	convnext_small_imagenet_100_seed-0	.412
242	inception_v1	.412
243	resnet-152_v2-tf	.411
244	mobilenet_v2_1_3_224	.411
245	alexnet_random_l2_3_perturb	.409
246	mobilenet_v1_1.0_224	.409
247	texture_shape_resnet50_trained_on_SIN	.409
248	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.407
249	resnet18_imagenet_full	.407
250	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.407
251	mobilenet_v1_0.75_128	.407
252	mobilenet_v1_0.5_160	.407
253	densenet-121	.406
254	resnet_SIN_IN_FT_IN	.406
255	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.406
256	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.406
257	resnet18_ecoset_full	.406
258	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.406
259	CLIP_resnet50_float32	.405
260	CLIP_resnet50	.405
261	alexnet_ks_torevert	.405
262	alexnet	.405
263	grcnn_v2_text_noise	.405
264	vit_large_patch14_clip_224:laion2b_ft_in1k	.403
265	ReAlnet01_cornet_fov4	.403
266	resnet50_simclr	.403
267	resnet18-deepcluster	.402
268	densenet-121-keras	.402
269	resnet18-local_aggregation	.402
270	resnet18_imagenet21kP	.401
271	RN50	.401
272	mobilenet_v1_0.5_224	.401
273	resnet_50_v1_spiking_l3	.401
274	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.401
275	alexnet_random_linf8_perturb	.400
276	BiT-S-R152x2	.400
277	mobilenet_v2_0_5_224	.400
278	vit_large_patch14_clip_224:openai_ft_in1k	.399
279	mobilenet_v1_0.25_128	.399
280	CORnet-Z	.397
281	deit_small_imagenet_100_seed-0	.395
282	CLIP-RN50	.395
283	convnext_femto_ols:d1_in1k	.394
284	mobilenet_v1_0.25_224	.394
285	resnet18-supervised	.393
286	BiT-S-R50x3	.393
287	BiT-M-R50x3	.393
288	squeezenet1_1	.392
289	vonealexnet_gaussian_noise_std4_fixed	.392
290	deepeisnn_ei_imagenet_resnet18	.392
291	inception_resnet_v2	.390
292	resnet50_moco_v2	.390
293	vgg-16-keras	.389
294	resnet_50_v2	.387
295	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.385
296	vgg_16	.384
297	resnet34_imagenet_full	.384
298	xception-keras	.384
299	resnext101_32x48d_wsl	.383
300	resnet50_byol	.383
301	alexnet_fov12	.383
302	alexnet_fov4	.383
303	convnext_tiny_sup	.381
304	RN50	.381
305	inception_v2-tf	.380
306	vgg_19	.379
307	alexnet_reduced_aliasing_early_checkpoint	.379
308	BiT-M-R50x1	.378
309	vit_base_patch16_clip_224:openai_ft_in1k	.378
310	resnext101_32x16d_wsl	.377
311	r3m_resnet18	.377
312	resnet-18_test_m	.377
313	resnet-18	.377
314	inception_v3	.376
315	resnet50_primary_visual_cortex	.376
316	VOneCORnet-S	.375
317	AlexNet_SIN_fov16	.374
318	vgg-19-keras	.373
319	briaai_rmbg_1_4	.371
320	artResNet18_1	.371
321	resnet-34	.368
322	alexnet_fov16	.368
323	resnext101_32x32d_wsl	.368
324	alexnet_early_checkpoint	.368
325	blt_vs	.367
326	convnext_base_fb_in1k_gram_aligned_dinov3	.366
327	BiT-S-R50x1	.366
328	AlexNet_SIN	.365
329	inception_v3-tf	.364
330	r3m_resnet34	.364
331	vit_large_patch14_clip_336:laion2b_ft_in1k	.364
332	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.364
333	pnasnet_large_halfPrecision	.363
334	yudixie_resnet50_object_class_0_240908	.362
335	resnet18-colorization	.361
336	SWSL_resnext101_32x8d	.360
337	resnet18_fair	.360
338	AlexNet_SIN_fov12	.358
339	resnet18-contrastive_multiview	.356
340	vit_base_patch14_dinov2-lvd142m	.356
341	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.354
342	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.353
343	texture_shape_alexnet_trained_on_SIN	.353
344	pnasnet_large-tf	.353
345	vit_base_patch16_dinov3-lvd1689m	.350
346	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.347
347	yolos_tiny	.346
348	pr1_stl10_disentangled_alpha04	.345
349	resnet18-relative_position	.342
350	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.342
351	yudixie_resnet50_category_class_0_240908	.340
352	BiT-M-R101x1	.337
353	AlexNet_SIN_fov4	.335
354	BiT-M-R101x3	.334
355	BiT-S-R101x1	.332
356	BiT-S-R101x3	.330
357	inception_v4-tf	.328
358	BiT-M-R152x2	.327
359	ReAlnet06	.325
360	ReAlnet05	.323
361	ReAlnet07	.323
362	ReAlnet04	.322
363	ReAlnet10	.321
364	ReAlnet01	.321
365	ReAlnet03	.320
366	ReAlnet08	.320
367	squeezenet1_0	.320
368	ReAlnet09	.319
369	resnet18-contrastive_predictive	.318
370	resnet50_imagenet_10_seed-0	.318
371	ReAlnet02	.317
372	aughost_fair_resnet18	.317
373	r3m_resnet50	.315
374	yudixie_resnet50_distance_reg_0_240908	.313
375	vggface	.313
376	yudixie_resnet50_translation_rotation_0_240908	.313
377	vit_base_patch14_reg4_dinov2-lvd142m	.312
378	yudixie_resnet18_category_class_0_240719	.312
379	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.311
380	cornet_s	.311
381	resnet50-cifar	.310
382	deepeisnn_ei_cifar10_resnet18	.309
383	predictive_coding_pc	.308
384	yudixie_resnet50_distance_translation_rotation_0_240908	.307
385	yudixie_resnet18_object_class_0_240719	.306
386	yudixie_resnet50_distance_rotation_0_240908	.306
387	deit3_base_patch16_224_fb_in22k_ft_in1k	.305
388	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.305
389	resnet-152_v2_pytorch	.305
390	yudixie_resnet50_distance_translation_0_240908	.296
391	yudixie_resnet50_translation_reg_0_240908	.295
392	yudixie_resnet50_rotation_reg_0_240908	.295
393	resnet18-depth_prediction	.291
394	deepeisnn_ei_cifar10_vgg19	.289
395	CORnetZ_CIFAR10	.286
396	resnet50	.284
397	alexnet_training_seed_02	.277
398	alexnet_training_seed_06	.276
399	alexnet_training_seed_03	.273
400	alexnet_training_seed_08	.271
401	alexnet_training_seed_05	.268
402	alexnet_training_seed_01	.266
403	alexnet_training_seed_10	.263
404	alexnet_training_seed_09	.262
405	alexnet_training_seed_04	.260
406	resnet50_FractalDB	.259
407	compact_resnet50_robust_IT	.258
408	alexnet_training_seed_01_fov12	.258
409	compact_resnet50_IT	.256
410	prednet	.256
411	mobilevit_small	.254
412	alexnet_training_seed_07	.254
413	yudixie_resnet18_translation_rotation_0_240719	.253
414	compact_cornets_IT	.247
415	my-model	.243
416	alexnet_training_seed_01_fov16	.240
417	yudixie_resnet18_distance_rotation_0_240719	.238
418	yudixie_resnet18_distance_translation_0_240719	.234
419	compact_vgg19_IT	.233
420	yudixie_resnet18_translation_reg_0_240719	.230
421	yudixie_resnet18_distance_translation_rotation_0_240719	.230
422	resnet-50x2_untrained	.228
423	yudixie_resnet18_rotation_reg_0_240719	.223
424	alexnet_training_seed_01_fov4	.221
425	convnext_small_imagenet_10_seed-0	.220
426	yudixie_resnet18_distance_reg_0_240719	.219
427	CORnetZ_CIFAR10_bs32_20_04	.215
428	resnet50_imagenet_1_seed-0	.215
429	convnext_base_fb_in22k_ft_in1k	.212
430	yudixie_resnet50_random_0_240908	.209
431	yudixie_wbh_object_class_scaling_0415_run_0	.205
432	yudixie_resnet18_random_0_240719	.204
433	resnet50-meshes-lt-100-original-scratch	.204
434	yudixie_wbh_object_class_scaling_0415_run_2	.197
435	resnet-18_untrained	.191
436	resnet18-autoencoder	.190
437	yudixie_wbh_object_class_scaling_0415_run_1	.187
438	yudixie_wbh_object_class_scaling_0415_run_3	.181
439	resnet50_pretrained_with_retinal_waves	.178
440	convnext_base_fb_in1k	.176
441	resnet-50_untrained	.176
442	resnet-18-LC_untrained	.166
443	compact_cornets_V4	.165
444	v1-pyr-nodown	.163
445	resnet50-meshes-lt-100-original-pretrained	.150
446	compact_vgg19_V4	.124
447	compact_resnet50_robust_V4	.111
448	compact_resnet50_V4	.102
449	deit_small_imagenet_1_seed-0	.049
450	deit_small_imagenet_10_seed-0	.045
451	convnext_small_imagenet_1_seed-0	.036
452	pixels	.033
453	my-model	.019

Benchmark bibtex

@misc{Sanghavi_Jozwik_DiCarlo_2021,
  title={SanghaviJozwik2020},
  url={osf.io/fhy36},
  DOI={10.17605/OSF.IO/FHY36},
  publisher={OSF},
  author={Sanghavi, Sachi and Jozwik, Kamila M and DiCarlo, James J},
  year={2021},
  month={Nov}
}

Ceiling

0.86.

Note that scores are relative to this ceiling.

Data: SanghaviJozwik2020.IT

4916 stimuli recordings from 26 sites in IT

Metric: pls