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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("SanghaviJozwik2020.V4-pls")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	ReAlnet01_cornet_fov4	.536
2	mehrer2020_alexnet_training_seed_01_fov4	.529
3	FrankRobWobv0	.528
4	custom_model_cv_18_dagger_408	.520
5	alexnet_fov4	.511
6	resnet50	.507
7	resnet50_ewconplus_wzc_seed6_2_323	.507
8	resnet50_random_l2_perturb	.507
9	SWSL_resnet50	.505
10	resnet50_ewconplus_wzc_seed5_2__323	.502
11	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.499
12	cv_18_dagger_408_pretrained	.498
13	dinov2_vitg14_lc	.497
14	vit_base_patch16_clip_224:openai_ft_in1k	.496
15	resnet50_ewconplus_wzc_seed2_2__323	.496
16	antialiased-r50	.495
17	resnet50_st_wzc_seed6_2_323	.494
18	texture_shape_resnet50_trained_on_SIN	.493
19	resnext101_32x16d_wsl	.493
20	antialiased-rnext101_32x8d	.493
21	resnet50_random_linf8_perturb	.492
22	SWSL_resnext101_32x8d	.492
23	vit_relpos_base_patch16_clsgap_224:sw_in1k	.492
24	dinov2_vitl14_reg_lc	.492
25	dinov2_vitl14_reg_lc_featread	.492
26	resnet50-SIN_IN_IN	.492
27	resnet_SIN_IN_FT_IN	.492
28	yudixie_resnet50_imagenet1kpret_0_240312	.491
29	resnet50_tutorial	.491
30	resnet_50_v1	.491
31	resnet50-sup	.491
32	yudixie_resnet50_imagenet1kpret_0_240908	.491
33	resnet_50_v1_spiking	.491
34	resnet_50_v1_spiking_l4	.491
35	resnet_50_v1_spiking_l4a	.491
36	resnet_50_v1_spiking_l3	.491
37	resnet152_imagenet_full	.491
38	resnet101_imagenet_full	.491
39	dinov2_vitg14_reg_lc	.490
40	vit_large_clip336_openai	.490
41	resnet152_ecoset_full	.489
42	resnet_50_v2	.489
43	ReAlnet10_cornet	.489
44	ReAlnet08_cornet	.488
45	resnet101_ecoset_full	.488
46	nasnet_mobile	.488
47	resnet-101_v1-tf	.488
48	deit_small_imagenet_full_seed-0	.487
49	resnet50-SIN_IN	.487
50	cvt_cvt-13-224-in1k_4_LucyV4	.486
51	ReAlnet02_cornet	.486
52	Res2Net50_26w_4s	.486
53	deit_large_imagenet_full_seed-0	.485
54	regnety_032	.485
55	cvt_cvt-21-384-in1k_4_LucyV4	.485
56	resnet50_linf_4_robust	.485
57	ReAlnet07_cornet	.485
58	ReAlnet06_cornet	.485
59	resnet50_st_wzc_seed7_2_323	.485
60	ReAlnet05_cornet	.484
61	ReAlnet09_cornet	.484
62	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.484
63	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.484
64	deit3_base_patch16_224_fb_in1k	.484
65	ReAlnet04_cornet	.484
66	ReAlnet01_cornet	.484
67	resnet-152_v1-tf	.483
68	ReAlnet03_cornet	.483
69	resnet101	.483
70	resnext101_32x8d_wsl	.483
71	resnet50_ewconplus_wzc	.483
72	AdvProp_efficientnet-b4	.483
73	effnetb1_272x240	.483
74	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.483
75	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.482
76	pnasnet_large-tf	.482
77	cvt_cvt-13-384-in1k_4_LucyV4	.481
78	convnext_tiny_imagenet_full_seed-0	.481
79	resnet50_st_wzc_seed3_2_323	.481
80	deit3_base_patch16_224_fb_in22k_ft_in1k	.481
81	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.481
82	resnet50-VITO-8deg-cc	.481
83	resnet50_hvs_wzc	.480
84	vision_transformer_vit_large_patch16_224	.480
85	CLIP-RN50	.480
86	inception_v2-tf	.479
87	ReAlnet07_ALL	.479
88	resnet50_l2_3_robust	.478
89	cvt_cvt-21-224-in1k_4_LucyV4	.478
90	resnet50_moco_v2	.478
91	ReAlnet08_ALL	.477
92	dinov2_vitl14_lc_res336	.477
93	ReAlnet05_ALL	.477
94	resnet-50_v1-tf	.477
95	ReAlnet02_ALL	.477
96	ReAlnet01_ALL	.476
97	ReAlnet09_ALL	.476
98	eBarlow_lmda_02_1000ep	.476
99	ReAlnet03_ALL	.476
100	ReAlnet10_ALL	.476
101	ReAlnet06_ALL	.476
102	convnext_xlarge:fb_in22k_ft_in1k	.476
103	voneresnet-50	.476
104	ReAlnet04_ALL	.475
105	omnivore_swinT	.475
106	resnet18_imagenet_full	.475
107	omnivore_swinB	.475
108	resnet50_primary_visual_cortex	.475
109	mobilenet_v2_1_3_224	.475
110	resnet18_ecoset_full	.475
111	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.475
112	vonegrcnn_62e_nobn	.474
113	densenet-201	.474
114	seresnext50_32x4d	.474
115	omnivore_swinS	.474
116	densenet-121-keras	.473
117	AlexNet_SIN_fov4	.473
118	xception-keras	.473
119	cornet_s	.473
120	convnext_small_imagenet_full_seed-0	.473
121	vonegrcnn_52e_full	.473
122	convnext_large_imagenet_full_seed-0	.472
123	vonegrcnn_47e	.472
124	CORnet-S	.472
125	AdvProp_efficientnet-b0	.472
126	tv_efficientnet-b1	.472
127	focalnet_tiny_lrf_in1k	.472
128	resnet50-vicreg	.472
129	convnext_large:fb_in22k_ft_in1k	.471
130	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.471
131	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.471
132	resnext101_32x32d_wsl	.471
133	resnet50_byol	.471
134	eicircuit_resnet18_bn_20260919	.471
135	densenet-169	.470
136	convnext_large_in22k_supervised	.470
137	mobilenet_v2_1_0_224	.470
138	efficientnet_b2_imagenet_full	.470
139	barlow-twins-resnet50	.470
140	nasnet_mobile-tf	.470
141	resnext101_32x48d_wsl	.470
142	resnet50_imagenet_100_seed-0	.470
143	inception_v1-tf	.470
144	mobilenet_v1_0.75_128	.470
145	effnetv2m_custom384	.469
146	resnet50-barlow	.469
147	resnet50-vicregl0p9	.469
148	CLIP_resnet50_float32	.469
149	CLIP_resnet50	.469
150	efficientnet_b0	.469
151	voneresnet-50-robust	.469
152	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.469
153	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.469
154	CLIP_ViT-B_32	.469
155	resnet50_st_wzc_2	.469
156	convnext_base_imagenet_full_seed-0	.469
157	mobilenet_v2_1_0_192	.469
158	VOneCORnet-S	.469
159	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.469
160	voneresnet-50-non_stochastic	.469
161	resnet50-moclr8deg	.469
162	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.468
163	resnet-18-LC_w_sh_10_iter_conv_init_m	.468
164	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.468
165	ViT-B/32	.467
166	convnext_femto_ols:d1_in1k	.467
167	dinov2_vitl14_lc	.467
168	antialias-resnet152	.467
169	convnext_tiny:in12k_ft_in1k	.466
170	densenet-169-keras	.466
171	AT_efficientnet-b7	.466
172	mobilenet_v1_1.0_224	.466
173	resnet-18-LC_w_sh_1_iter_conv_init_m	.465
174	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.465
175	AdvProp_efficientnet-b6	.465
176	resnet-50_v2-tf	.464
177	AdvProp_efficientnet-b7	.464
178	regnet_y_400mf	.464
179	resnet34_imagenet_full	.464
180	AT_efficientnet-b2	.464
181	convnext_tiny_sup	.464
182	resnet18_imagenet21kP	.463
183	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.463
184	resnet50-simclr-vissl	.463
185	mobilenet_v1_1.0_160	.463
186	resnet50-vicregl0p75	.463
187	resnet50_robust_l2_eps1	.463
188	nasnet_large-tf	.463
189	AdvProp_efficientnet-b8	.462
190	inception_v4-tf	.462
191	resnet-18-LC_w_sh_100_iter_conv_init_m	.462
192	inception_resnet_v2	.462
193	mobilenet_v1_0.5_128	.462
194	mobilenet_v1_1.0_128	.461
195	0.5x_resnet-18_LC_w_sh_10_iter	.461
196	resnet-101_v2-tf	.461
197	mobilenet_v1_1.0_192	.461
198	mobilenet_v1_0.75_224	.461
199	mobilenet_v1_0.75_160	.461
200	AdvProp_efficientnet-b2	.460
201	grcnn_109	.460
202	resnet50_linf_8_robust	.460
203	resnet-18-LC_w_sh_100_iter_m	.460
204	mobilenet_v1_0.5_192	.460
205	AT_efficientnet-b4	.459
206	resnet50-SIN	.459
207	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.459
208	resnet50_robust_l2_eps3	.459
209	resnet-18-LC_w_sh_1_iter_m	.459
210	inception_v3-tf	.459
211	convnext_large_clip_laion2b_finelayers	.459
212	convnext_xxlarge_clip	.459
213	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.459
214	resnet50-vitoimagevidnet8	.458
215	inception_v3	.458
216	resnet50_imagenet_full	.458
217	0.5x_resnet-18_LC_w_sh_1_iter	.458
218	imagenet_l2_3_0	.457
219	mobilenet_v2_1_4_224	.457
220	inception_v1	.457
221	yudixie_resnet18_imagenet1kpret_0_240719	.456
222	yudixie_wbh_object_class_scaling_0415_imagenet	.456
223	densenet-201-keras	.456
224	mobilenet_v2_1.3_224-tf	.456
225	efficientnet_b0_imagenet_full	.456
226	grcnn_v2_text_noise	.455
227	resnet50_ecoset_full	.455
228	vit_base_patch14_dinov2-lvd142m	.455
229	ReAlnet01_cornet_fov12	.455
230	mobilenet_v2_0.75_224-tf	.455
231	resnet34_ecoset_full	.455
232	grcnn	.455
233	mobilenet_v2_1.4_224-tf	.454
234	mobilenet_v2_0_75_192	.454
235	mobilenet_v1_0.5_160	.454
236	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.453
237	resnet-18-LC_d_w_sh_1x1_conv_init_m	.453
238	resnet-18	.452
239	vit_base_patch16_dinov3-lvd1689m	.452
240	mobilenet_v1_0.5_224	.452
241	resnet50_simclr	.452
242	efficientnet_b1_imagenet_full	.452
243	grcnn_robust_v1	.452
244	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.452
245	mobilenet_v2_0_75_224	.452
246	mobilenet_v2_1.0_224-tf	.452
247	resnet50_barlowtwins_linhead	.451
248	resnet-152_v2-tf	.451
249	resnet50_simclr_linhead_01norm	.449
250	mobilenet_v2_1_0_160	.449
251	resnet50_vicreg_linhead	.449
252	convnext_small_imagenet_100_seed-0	.448
253	vit_large_patch14_clip_224:openai_ft_in1k	.448
254	mobilenet_v1_0.75_192	.448
255	mobilenet_v2_0_75_160	.447
256	mobilenet_v1_0.25_224	.447
257	shufflenet_v2_x1_0	.446
258	alexnet_random_linf8_perturb	.446
259	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.446
260	vit_large_patch14_clip_224:laion2b_ft_in1k	.446
261	mobilenet_v2_1_0_128	.445
262	mobilenet_v2_0_5_224	.445
263	RN50	.445
264	alexnet_random_l2_3_perturb	.444
265	mobilenet_v1_0.25_192	.444
266	BiT-M-R101x3	.444
267	blt_vs	.443
268	mobilenet_v2_0_5_192	.442
269	ReAlnet08	.442
270	convnext_base:clip_laiona_augreg_ft_in1k_384	.442
271	vgg_16	.441
272	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.441
273	deepeisnn_ei_imagenet_resnet18	.441
274	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.441
275	resnet18-supervised	.440
276	BiT-M-R50x1	.440
277	mobilenet_v2_0.5_224-tf	.439
278	deit_base_imagenet_full_seed-0	.439
279	densenet-121	.439
280	BiT-S-R50x3	.439
281	0.5x_resnet-18	.439
282	vgg_19	.439
283	resnet-18_test_m	.439
284	konkle_alexnetgn_ipcl_ref01_primary_model	.438
285	efficientnet-b7	.438
286	ReAlnet10	.438
287	mobilenet_v2_0.75_160-tf	.438
288	resnet50_byol_linhead	.438
289	vit_large_patch14_clip_336:laion2b_ft_in1k	.437
290	ReAlnet02	.437
291	BiT-M-R101x1	.436
292	resnet50_simsiam_linhead	.435
293	ReAlnet06	.435
294	mehrer2020_alexnet_training_seed_04	.435
295	vgg-16-keras	.435
296	ReAlnet05	.435
297	0.5x_resnet-18_LC_w_sh_100_iter	.435
298	mobilenet_v2_1.0_96	.434
299	mobilenet_v2_1.0_128-tf	.434
300	ReAlnet09	.434
301	mehrer2020_alexnet_training_seed_02	.433
302	ReAlnet07	.433
303	ReAlnet01	.432
304	RN50	.432
305	mehrer2020_alexnet_training_seed_05	.431
306	ReAlnet04	.431
307	mehrer2020_alexnet_training_seed_03	.431
308	resnet-50-pytorch	.431
309	resnet-50-robust	.431
310	ReAlnet03	.430
311	mobilenet_v2_0.75_96	.430
312	resnet-18-LC_w_sh_10_iter_m	.430
313	ijepa_vith14_linhead	.430
314	resnet18-instance_recognition	.430
315	resnet18_fair	.430
316	CORnet-Z	.430
317	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.429
318	yudixie_resnet50_object_class_0_240908	.429
319	mehrer2020_alexnet_training_seed_07	.429
320	resnet18-local_aggregation	.427
321	mehrer2020_alexnet_training_seed_08	.427
322	mobilenet_v1_0.25_160	.427
323	vonealexnet_gaussian_noise_std4_fixed	.427
324	imagenet_l2_10_0	.427
325	mehrer2020_alexnet_training_seed_06	.426
326	BiT-S-R101x3	.426
327	mehrer2020_alexnet_training_seed_01	.426
328	mobilenet_v1_0.25_128	.426
329	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.426
330	mehrer2020_alexnet_training_seed_09	.425
331	mobilenet_v2_0.5_128	.425
332	squeezenet1_0	.424
333	mobilenet_v2_1.0_160-tf	.424
334	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.424
335	mobilenet_v2_1.0_192-tf	.423
336	mobilenet_v2_0.75_128	.422
337	BiT-S-R50x1	.422
338	alexnet	.421
339	alexnet_ks_torevert	.421
340	BiT-M-R152x4	.421
341	squeezenet1_1	.421
342	mobilenet_v2_0.35_224	.421
343	BiT-M-R50x3	.420
344	resnet18-colorization	.420
345	mehrer2020_alexnet_training_seed_10	.419
346	yudixie_resnet50_category_class_0_240908	.419
347	alexnet_l2_3_robust	.418
348	convnext_base_fb_in22k_ft_in1k	.418
349	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.418
350	vgg-19-keras	.417
351	BiT-S-R101x1	.416
352	yolos_tiny	.416
353	mobilenet_v2_0.75_192-tf	.415
354	ReAlnet01_cornet_fov16	.415
355	resnet18-relative_position	.415
356	mobilenet_v2_0.5_96	.414
357	yudixie_resnet50_distance_translation_rotation_0_240908	.414
358	BiT-M-R152x2	.414
359	yudixie_resnet50_translation_rotation_0_240908	.413
360	vit_base_patch14_reg4_dinov2-lvd142m	.413
361	texture_shape_alexnet_trained_on_SIN	.413
362	yudixie_resnet50_distance_rotation_0_240908	.413
363	deit_small_imagenet_100_seed-0	.411
364	yudixie_resnet50_distance_translation_0_240908	.411
365	yudixie_resnet50_translation_reg_0_240908	.409
366	resnet18-contrastive_multiview	.408
367	resnet-34	.408
368	mobilenet_v2_0.5_160	.407
369	mobilenet_v2_0.35_192	.405
370	resnet-18-LC_m	.405
371	yudixie_resnet18_object_class_0_240719	.405
372	mobilenet_v2_0.35_96	.404
373	mobilenet_v2_0.35_160	.403
374	mobilenet_v2_0.5_192-tf	.402
375	AlexNet_SIN	.402
376	alexnet_reduced_aliasing_early_checkpoint	.399
377	0.5x_resnet-18_LC	.399
378	BiT-S-R152x2	.399
379	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.399
380	convnext_base_fb_in1k	.399
381	convnext_base_fb_in1k_gram_aligned_dinov3	.399
382	yudixie_resnet50_distance_reg_0_240908	.399
383	artResNet18_1	.396
384	alexnet_early_checkpoint	.396
385	r3m_resnet18	.393
386	yudixie_resnet50_rotation_reg_0_240908	.391
387	r3m_resnet50	.391
388	resnet18-deepcluster	.390
389	r3m_resnet34	.389
390	BiT-S-R152x4	.389
391	compact_resnet50_IT	.386
392	yudixie_resnet18_category_class_0_240719	.386
393	ViT_L_32_imagenet1k	.380
394	mobilenet_v2_0.35_128	.379
395	resnet50-cifar	.378
396	yudixie_resnet18_distance_rotation_0_240719	.377
397	alexnet_training_seed_01_fov4	.377
398	compact_resnet50_robust_V4	.376
399	mehrer2020_alexnet_training_seed_01_fov12	.376
400	mobilenet_v2_1-4_224_pytorch	.370
401	yudixie_resnet18_distance_translation_0_240719	.368
402	yudixie_resnet18_distance_translation_rotation_0_240719	.366
403	resnet18-depth_prediction	.366
404	yudixie_resnet18_distance_reg_0_240719	.365
405	compact_resnet50_robust_IT	.362
406	resnet-18-LC_1st_conv_m	.361
407	prednet	.360
408	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.360
409	yudixie_resnet18_translation_rotation_0_240719	.358
410	alexnet_linf_8_robust	.357
411	yudixie_resnet18_translation_reg_0_240719	.356
412	vggface	.354
413	AlexNet_SIN_fov12	.347
414	yudixie_resnet18_rotation_reg_0_240719	.347
415	resnet-18-LC_conv_init_m	.347
416	deepeisnn_ei_cifar10_resnet18	.347
417	mehrer2020_alexnet_training_seed_01_fov16	.341
418	alexnet_fov12	.338
419	deepeisnn_ei_cifar10_vgg19	.337
420	resnet50_imagenet_10_seed-0	.336
421	compact_vgg19_V4	.335
422	my-model	.334
423	compact_resnet50_V4	.331
424	alexnet_robust_correct	.325
425	AlexNet_SIN_fov16	.307
426	alexnet_fov16	.306
427	compact_cornets_IT	.296
428	compact_cornets_V4	.288
429	gabor_filter_entropy_4x4_v2	.287
430	resnet18-contrastive_predictive	.285
431	yudixie_wbh_object_class_scaling_0415_run_0	.285
432	gabor_filter_entropy_4x4_v2_forcedCosine	.285
433	briaai_rmbg_1_4	.280
434	compact_vgg19_IT	.278
435	yudixie_wbh_object_class_scaling_0415_run_1	.273
436	alexnet_training_seed_02	.271
437	alexnet_training_seed_06	.271
438	CORnetZ_CIFAR10	.266
439	yudixie_wbh_object_class_scaling_0415_run_2	.265
440	alexnet_training_seed_01	.265
441	resnet18-autoencoder	.265
442	alexnet_training_seed_09	.265
443	alexnet_training_seed_10	.264
444	alexnet_training_seed_07	.262
445	alexnet_training_seed_05	.260
446	resnet-50x2_untrained	.260
447	alexnet_training_seed_04	.258
448	alexnet_training_seed_08	.258
449	alexnet_training_seed_03	.257
450	yudixie_wbh_object_class_scaling_0415_run_3	.241
451	resnet-50_untrained	.241
452	CORnetZ_CIFAR10_bs32_20_04	.240
453	alexnet_training_seed_01_fov12	.238
454	yudixie_resnet50_random_0_240908	.237
455	resnet-18_untrained	.236
456	yudixie_resnet18_random_0_240719	.235
457	v1-pyr-nodown	.235
458	gabor_filter_mean_abs_4x4_v2	.231
459	resnet50_pretrained_with_retinal_waves	.227
460	hmax	.216
461	alexnet_training_seed_01_fov16	.210
462	resnet-18-LC_untrained	.193
463	resnet50_imagenet_1_seed-0	.191
464	resnet50_FractalDB	.186
465	resnet-152_v2_pytorch	.184
466	pr1_stl10_disentangled_alpha04	.181
467	gabor_filter_entropy_4x4	.173
468	predictive_coding_pc	.155
469	convnext_small_imagenet_10_seed-0	.066
470	deit_small_imagenet_10_seed-0	.053
471	deit_small_imagenet_1_seed-0	.037
472	convnext_small_imagenet_1_seed-0	.035
473	pixels	.024
474	my-model	.020
475	pnasnet_large_halfPrecision
476	eva02_large_in22k
477	vit_huge_clip336_laion

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

0.96.

Note that scores are relative to this ceiling.

Data: SanghaviJozwik2020.V4

4916 stimuli recordings from 50 sites in V4

Metric: pls