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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_random_l2_perturb	.507
7	SWSL_resnet50	.505
8	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.499
9	cv_18_dagger_408_pretrained	.498
10	vit_base_patch16_clip_224:openai_ft_in1k	.496
11	antialiased-r50	.495
12	texture_shape_resnet50_trained_on_SIN	.493
13	resnext101_32x16d_wsl	.493
14	antialiased-rnext101_32x8d	.493
15	resnet50_random_linf8_perturb	.492
16	SWSL_resnext101_32x8d	.492
17	vit_relpos_base_patch16_clsgap_224:sw_in1k	.492
18	resnet50-SIN_IN_IN	.492
19	resnet_SIN_IN_FT_IN	.492
20	yudixie_resnet50_imagenet1kpret_0_240312	.491
21	resnet50_tutorial	.491
22	resnet_50_v1	.491
23	resnet50-sup	.491
24	yudixie_resnet50_imagenet1kpret_0_240908	.491
25	resnet_50_v1_spiking	.491
26	resnet_50_v1_spiking_l4	.491
27	resnet_50_v1_spiking_l4a	.491
28	resnet_50_v1_spiking_l3	.491
29	resnet152_imagenet_full	.491
30	resnet101_imagenet_full	.491
31	resnet152_ecoset_full	.489
32	resnet_50_v2	.489
33	ReAlnet10_cornet	.489
34	ReAlnet08_cornet	.488
35	resnet101_ecoset_full	.488
36	nasnet_mobile	.488
37	resnet-101_v1-tf	.488
38	deit_small_imagenet_full_seed-0	.487
39	resnet50-SIN_IN	.487
40	cvt_cvt-13-224-in1k_4_LucyV4	.486
41	ReAlnet02_cornet	.486
42	Res2Net50_26w_4s	.486
43	deit_large_imagenet_full_seed-0	.485
44	cvt_cvt-21-384-in1k_4_LucyV4	.485
45	resnet50_linf_4_robust	.485
46	ReAlnet07_cornet	.485
47	ReAlnet06_cornet	.485
48	ReAlnet05_cornet	.484
49	ReAlnet09_cornet	.484
50	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.484
51	ReAlnet04_cornet	.484
52	ReAlnet01_cornet	.484
53	resnet-152_v1-tf	.483
54	ReAlnet03_cornet	.483
55	resnet101	.483
56	resnext101_32x8d_wsl	.483
57	resnet50_ewconplus_wzc	.483
58	AdvProp_efficientnet-b4	.483
59	effnetb1_272x240	.483
60	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.483
61	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.482
62	pnasnet_large-tf	.482
63	cvt_cvt-13-384-in1k_4_LucyV4	.481
64	convnext_tiny_imagenet_full_seed-0	.481
65	resnet50-VITO-8deg-cc	.481
66	vision_transformer_vit_large_patch16_224	.480
67	CLIP-RN50	.480
68	inception_v2-tf	.479
69	ReAlnet07_ALL	.479
70	resnet50_l2_3_robust	.478
71	cvt_cvt-21-224-in1k_4_LucyV4	.478
72	resnet50_moco_v2	.478
73	ReAlnet08_ALL	.477
74	ReAlnet05_ALL	.477
75	resnet-50_v1-tf	.477
76	ReAlnet02_ALL	.477
77	ReAlnet01_ALL	.476
78	ReAlnet09_ALL	.476
79	eBarlow_lmda_02_1000ep	.476
80	ReAlnet03_ALL	.476
81	ReAlnet10_ALL	.476
82	ReAlnet06_ALL	.476
83	convnext_xlarge:fb_in22k_ft_in1k	.476
84	voneresnet-50	.476
85	ReAlnet04_ALL	.475
86	omnivore_swinT	.475
87	resnet18_imagenet_full	.475
88	omnivore_swinB	.475
89	resnet50_primary_visual_cortex	.475
90	mobilenet_v2_1_3_224	.475
91	resnet18_ecoset_full	.475
92	vonegrcnn_62e_nobn	.474
93	densenet-201	.474
94	omnivore_swinS	.474
95	densenet-121-keras	.473
96	AlexNet_SIN_fov4	.473
97	xception-keras	.473
98	cornet_s	.473
99	convnext_small_imagenet_full_seed-0	.473
100	vonegrcnn_52e_full	.473
101	convnext_large_imagenet_full_seed-0	.472
102	vonegrcnn_47e	.472
103	CORnet-S	.472
104	AdvProp_efficientnet-b0	.472
105	tv_efficientnet-b1	.472
106	focalnet_tiny_lrf_in1k	.472
107	resnet50-vicreg	.472
108	convnext_large:fb_in22k_ft_in1k	.471
109	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.471
110	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.471
111	resnext101_32x32d_wsl	.471
112	resnet50_byol	.471
113	densenet-169	.470
114	mobilenet_v2_1_0_224	.470
115	efficientnet_b2_imagenet_full	.470
116	barlow-twins-resnet50	.470
117	nasnet_mobile-tf	.470
118	resnext101_32x48d_wsl	.470
119	resnet50_imagenet_100_seed-0	.470
120	inception_v1-tf	.470
121	mobilenet_v1_0.75_128	.470
122	effnetv2m_custom384	.469
123	resnet50-barlow	.469
124	resnet50-vicregl0p9	.469
125	CLIP_resnet50_float32	.469
126	CLIP_resnet50	.469
127	efficientnet_b0	.469
128	voneresnet-50-robust	.469
129	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.469
130	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.469
131	CLIP_ViT-B_32	.469
132	convnext_base_imagenet_full_seed-0	.469
133	mobilenet_v2_1_0_192	.469
134	VOneCORnet-S	.469
135	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.469
136	voneresnet-50-non_stochastic	.469
137	resnet50-moclr8deg	.469
138	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.468
139	resnet-18-LC_w_sh_10_iter_conv_init_m	.468
140	ViT-B/32	.467
141	convnext_femto_ols:d1_in1k	.467
142	antialias-resnet152	.467
143	convnext_tiny:in12k_ft_in1k	.466
144	densenet-169-keras	.466
145	AT_efficientnet-b7	.466
146	mobilenet_v1_1.0_224	.466
147	resnet-18-LC_w_sh_1_iter_conv_init_m	.465
148	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.465
149	AdvProp_efficientnet-b6	.465
150	resnet-50_v2-tf	.464
151	AdvProp_efficientnet-b7	.464
152	regnet_y_400mf	.464
153	resnet34_imagenet_full	.464
154	AT_efficientnet-b2	.464
155	convnext_tiny_sup	.464
156	resnet18_imagenet21kP	.463
157	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.463
158	resnet50-simclr-vissl	.463
159	mobilenet_v1_1.0_160	.463
160	resnet50-vicregl0p75	.463
161	resnet50_robust_l2_eps1	.463
162	nasnet_large-tf	.463
163	AdvProp_efficientnet-b8	.462
164	inception_v4-tf	.462
165	resnet-18-LC_w_sh_100_iter_conv_init_m	.462
166	inception_resnet_v2	.462
167	mobilenet_v1_0.5_128	.462
168	mobilenet_v1_1.0_128	.461
169	0.5x_resnet-18_LC_w_sh_10_iter	.461
170	resnet-101_v2-tf	.461
171	mobilenet_v1_1.0_192	.461
172	mobilenet_v1_0.75_224	.461
173	mobilenet_v1_0.75_160	.461
174	AdvProp_efficientnet-b2	.460
175	grcnn_109	.460
176	resnet50_linf_8_robust	.460
177	resnet-18-LC_w_sh_100_iter_m	.460
178	mobilenet_v1_0.5_192	.460
179	AT_efficientnet-b4	.459
180	resnet50-SIN	.459
181	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.459
182	resnet50_robust_l2_eps3	.459
183	resnet-18-LC_w_sh_1_iter_m	.459
184	inception_v3-tf	.459
185	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.459
186	resnet50-vitoimagevidnet8	.458
187	inception_v3	.458
188	resnet50_imagenet_full	.458
189	0.5x_resnet-18_LC_w_sh_1_iter	.458
190	imagenet_l2_3_0	.457
191	mobilenet_v2_1_4_224	.457
192	inception_v1	.457
193	yudixie_resnet18_imagenet1kpret_0_240719	.456
194	densenet-201-keras	.456
195	mobilenet_v2_1.3_224-tf	.456
196	efficientnet_b0_imagenet_full	.456
197	grcnn_v2_text_noise	.455
198	resnet50_ecoset_full	.455
199	vit_base_patch14_dinov2-lvd142m	.455
200	ReAlnet01_cornet_fov12	.455
201	mobilenet_v2_0.75_224-tf	.455
202	resnet34_ecoset_full	.455
203	grcnn	.455
204	mobilenet_v2_1.4_224-tf	.454
205	mobilenet_v2_0_75_192	.454
206	mobilenet_v1_0.5_160	.454
207	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.453
208	resnet-18-LC_d_w_sh_1x1_conv_init_m	.453
209	resnet-18	.452
210	vit_base_patch16_dinov3-lvd1689m	.452
211	mobilenet_v1_0.5_224	.452
212	resnet50_simclr	.452
213	efficientnet_b1_imagenet_full	.452
214	grcnn_robust_v1	.452
215	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.452
216	mobilenet_v2_0_75_224	.452
217	mobilenet_v2_1.0_224-tf	.452
218	resnet-152_v2-tf	.451
219	mobilenet_v2_1_0_160	.449
220	convnext_small_imagenet_100_seed-0	.448
221	vit_large_patch14_clip_224:openai_ft_in1k	.448
222	mobilenet_v1_0.75_192	.448
223	mobilenet_v2_0_75_160	.447
224	mobilenet_v1_0.25_224	.447
225	shufflenet_v2_x1_0	.446
226	alexnet_random_linf8_perturb	.446
227	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.446
228	vit_large_patch14_clip_224:laion2b_ft_in1k	.446
229	mobilenet_v2_1_0_128	.445
230	mobilenet_v2_0_5_224	.445
231	RN50	.445
232	alexnet_random_l2_3_perturb	.444
233	mobilenet_v1_0.25_192	.444
234	BiT-M-R101x3	.444
235	blt_vs	.443
236	mobilenet_v2_0_5_192	.442
237	ReAlnet08	.442
238	convnext_base:clip_laiona_augreg_ft_in1k_384	.442
239	vgg_16	.441
240	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.441
241	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.441
242	resnet18-supervised	.440
243	BiT-M-R50x1	.440
244	mobilenet_v2_0.5_224-tf	.439
245	deit_base_imagenet_full_seed-0	.439
246	densenet-121	.439
247	BiT-S-R50x3	.439
248	0.5x_resnet-18	.439
249	vgg_19	.439
250	resnet-18_test_m	.439
251	konkle_alexnetgn_ipcl_ref01_primary_model	.438
252	efficientnet-b7	.438
253	ReAlnet10	.438
254	mobilenet_v2_0.75_160-tf	.438
255	vit_large_patch14_clip_336:laion2b_ft_in1k	.437
256	ReAlnet02	.437
257	BiT-M-R101x1	.436
258	ReAlnet06	.435
259	vgg-16-keras	.435
260	ReAlnet05	.435
261	0.5x_resnet-18_LC_w_sh_100_iter	.435
262	mobilenet_v2_1.0_96	.434
263	mobilenet_v2_1.0_128-tf	.434
264	ReAlnet09	.434
265	ReAlnet07	.433
266	ReAlnet01	.432
267	RN50	.432
268	ReAlnet04	.431
269	resnet-50-pytorch	.431
270	resnet-50-robust	.431
271	ReAlnet03	.430
272	mobilenet_v2_0.75_96	.430
273	resnet-18-LC_w_sh_10_iter_m	.430
274	resnet18-instance_recognition	.430
275	CORnet-Z	.430
276	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.429
277	yudixie_resnet50_object_class_0_240908	.429
278	resnet18-local_aggregation	.427
279	mobilenet_v1_0.25_160	.427
280	vonealexnet_gaussian_noise_std4_fixed	.427
281	imagenet_l2_10_0	.427
282	BiT-S-R101x3	.426
283	mobilenet_v1_0.25_128	.426
284	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.426
285	mobilenet_v2_0.5_128	.425
286	squeezenet1_0	.424
287	mobilenet_v2_1.0_160-tf	.424
288	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.424
289	mobilenet_v2_1.0_192-tf	.423
290	mobilenet_v2_0.75_128	.422
291	BiT-S-R50x1	.422
292	alexnet	.421
293	alexnet_ks_torevert	.421
294	BiT-M-R152x4	.421
295	squeezenet1_1	.421
296	mobilenet_v2_0.35_224	.421
297	BiT-M-R50x3	.420
298	resnet18-colorization	.420
299	yudixie_resnet50_category_class_0_240908	.419
300	alexnet_l2_3_robust	.418
301	vgg-19-keras	.417
302	BiT-S-R101x1	.416
303	yolos_tiny	.416
304	mobilenet_v2_0.75_192-tf	.415
305	ReAlnet01_cornet_fov16	.415
306	resnet18-relative_position	.415
307	mobilenet_v2_0.5_96	.414
308	yudixie_resnet50_distance_translation_rotation_0_240908	.414
309	BiT-M-R152x2	.414
310	yudixie_resnet50_translation_rotation_0_240908	.413
311	vit_base_patch14_reg4_dinov2-lvd142m	.413
312	texture_shape_alexnet_trained_on_SIN	.413
313	yudixie_resnet50_distance_rotation_0_240908	.413
314	deit_small_imagenet_100_seed-0	.411
315	yudixie_resnet50_distance_translation_0_240908	.411
316	yudixie_resnet50_translation_reg_0_240908	.409
317	resnet18-contrastive_multiview	.408
318	resnet-34	.408
319	mobilenet_v2_0.5_160	.407
320	mobilenet_v2_0.35_192	.405
321	resnet-18-LC_m	.405
322	yudixie_resnet18_object_class_0_240719	.405
323	mobilenet_v2_0.35_96	.404
324	mobilenet_v2_0.35_160	.403
325	mobilenet_v2_0.5_192-tf	.402
326	AlexNet_SIN	.402
327	alexnet_reduced_aliasing_early_checkpoint	.399
328	0.5x_resnet-18_LC	.399
329	BiT-S-R152x2	.399
330	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.399
331	yudixie_resnet50_distance_reg_0_240908	.399
332	artResNet18_1	.396
333	alexnet_early_checkpoint	.396
334	r3m_resnet18	.393
335	yudixie_resnet50_rotation_reg_0_240908	.391
336	r3m_resnet50	.391
337	resnet50	.391
338	resnet18-deepcluster	.390
339	r3m_resnet34	.389
340	BiT-S-R152x4	.389
341	compact_resnet50_IT	.386
342	yudixie_resnet18_category_class_0_240719	.386
343	ViT_L_32_imagenet1k	.380
344	mobilenet_v2_0.35_128	.379
345	resnet50-cifar	.378
346	yudixie_resnet18_distance_rotation_0_240719	.377
347	alexnet_training_seed_01_fov4	.377
348	compact_resnet50_robust_V4	.376
349	mobilenet_v2_1-4_224_pytorch	.370
350	yudixie_resnet18_distance_translation_0_240719	.368
351	yudixie_resnet18_distance_translation_rotation_0_240719	.366
352	resnet18-depth_prediction	.366
353	yudixie_resnet18_distance_reg_0_240719	.365
354	compact_resnet50_robust_IT	.362
355	resnet-18-LC_1st_conv_m	.361
356	prednet	.360
357	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.360
358	yudixie_resnet18_translation_rotation_0_240719	.358
359	alexnet_linf_8_robust	.357
360	yudixie_resnet18_translation_reg_0_240719	.356
361	vggface	.354
362	AlexNet_SIN_fov12	.347
363	yudixie_resnet18_rotation_reg_0_240719	.347
364	resnet-18-LC_conv_init_m	.347
365	alexnet_fov12	.338
366	resnet50_imagenet_10_seed-0	.336
367	compact_vgg19_V4	.335
368	my-model	.334
369	compact_resnet50_V4	.331
370	alexnet_robust_correct	.325
371	aughost_fair_resnet18	.308
372	AlexNet_SIN_fov16	.307
373	alexnet_fov16	.306
374	resnet50-meshes-lt-100-original-pretrained	.303
375	resnet50-meshes-lt-100-original-scratch	.296
376	compact_cornets_IT	.296
377	compact_cornets_V4	.288
378	resnet18-contrastive_predictive	.285
379	briaai_rmbg_1_4	.280
380	compact_vgg19_IT	.278
381	alexnet_training_seed_02	.271
382	alexnet_training_seed_06	.271
383	CORnetZ_CIFAR10	.266
384	alexnet_training_seed_01	.265
385	resnet18-autoencoder	.265
386	alexnet_training_seed_09	.265
387	alexnet_training_seed_10	.264
388	alexnet_training_seed_07	.262
389	alexnet_training_seed_05	.260
390	resnet-50x2_untrained	.260
391	alexnet_training_seed_04	.258
392	alexnet_training_seed_08	.258
393	alexnet_training_seed_03	.257
394	resnet-50_untrained	.241
395	CORnetZ_CIFAR10_bs32_20_04	.240
396	alexnet_training_seed_01_fov12	.238
397	yudixie_resnet50_random_0_240908	.237
398	resnet-18_untrained	.236
399	yudixie_resnet18_random_0_240719	.235
400	v1-pyr-nodown	.235
401	resnet50_pretrained_with_retinal_waves	.227
402	hmax	.216
403	alexnet_training_seed_01_fov16	.210
404	resnet-18-LC_untrained	.193
405	resnet50_imagenet_1_seed-0	.191
406	resnet50_FractalDB	.186
407	resnet-152_v2_pytorch	.184
408	convnext_small_imagenet_10_seed-0	.066
409	deit_small_imagenet_10_seed-0	.053
410	deit_small_imagenet_1_seed-0	.037
411	convnext_small_imagenet_1_seed-0	.035
412	pixels	.024
413	my-model	.020
414	pnasnet_large_halfPrecision

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