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

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