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