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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Sanghavi2020.IT-pls")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	eBarlow_lmda_02_1000ep	.495
2	resnet50-vicreg	.489
3	resnet50-barlow	.489
4	resnet50-vicregl0p9	.488
5	AdvProp_efficientnet-b7	.488
6	barlow-twins-resnet50	.487
7	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.487
8	AT_efficientnet-b7	.486
9	vonegrcnn_52e_full	.485
10	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.485
11	custom_model_cv_18_dagger_408	.483
12	vonegrcnn_62e_nobn	.483
13	AT_efficientnet-b2	.483
14	AdvProp_efficientnet-b4	.483
15	resnet50-vicregl0p75	.483
16	AT_efficientnet-b4	.482
17	AdvProp_efficientnet-b6	.482
18	AdvProp_efficientnet-b2	.482
19	AdvProp_efficientnet-b8	.481
20	konkle_alexnetgn_ipcl_ref01_primary_model	.481
21	efficientnet_b1_imagenet_full	.480
22	efficientnet_b2_imagenet_full	.480
23	AdvProp_efficientnet-b0	.480
24	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.480
25	efficientnet_b0_imagenet_full	.479
26	tv_efficientnet-b1	.479
27	resnet-18-LC_w_sh_10_iter_m	.479
28	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.479
29	convnext_tiny_imagenet_full_seed-0	.479
30	effnetv2m_custom384	.478
31	resnet-18-LC_w_sh_10_iter_conv_init_m	.478
32	0.5x_resnet-18_LC_w_sh_1_iter	.478
33	mobilenet_v2_1.0_192-tf	.477
34	resnet-152_v1-tf	.477
35	antialiased-rnext101_32x8d	.476
36	ReAlnet02_cornet	.476
37	resnet-101_v1-tf	.476
38	resnet-18-LC_w_sh_1_iter_conv_init_m	.476
39	resnet50_ewconplus_wzc	.475
40	resnet50-SIN_IN	.475
41	densenet-201-keras	.475
42	ReAlnet06_cornet	.474
43	efficientnet-b7	.474
44	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.474
45	resnet50_ewconplus_wzc_seed3_2_323	.474
46	mobilenet_v2_1.3_224-tf	.474
47	convnext_small_imagenet_full_seed-0	.473
48	mobilenet_v2_1.0_160-tf	.473
49	resnet50-moclr8deg	.473
50	mobilenet_v2_1.4_224-tf	.473
51	resnet-50_v1-tf	.473
52	resnet50_ewconplus_noseed_2_323	.473
53	ReAlnet03_cornet	.473
54	ReAlnet08_cornet	.473
55	ReAlnet04_cornet	.473
56	ReAlnet01_cornet	.473
57	resnet101_ecoset_full	.473
58	resnet50_ewconplus_wzc_seed5_2__323	.472
59	resnet50_ewconplus_wzc_seed6_2_323	.472
60	mobilenet_v2_0.75_224-tf	.471
61	ReAlnet07_cornet	.471
62	resnet50-simclr-vissl	.471
63	ReAlnet10_cornet	.471
64	resnet18-instance_recognition	.471
65	vit_relpos_base_patch16_clsgap_224:sw_in1k	.471
66	resnet50_robust_l2_eps1	.471
67	resnet50-SIN	.471
68	resnet50_ewconplus_wzc_seed7_2_323	.470
69	resnet-18-LC_w_sh_100_iter_conv_init_m	.470
70	effnetb1_272x240	.470
71	nasnet_mobile	.470
72	resnet50_imagenet_full	.470
73	mobilenet_v2_0.75_160-tf	.470
74	ReAlnet09_cornet	.470
75	resnet50_ewconplus_wzc_2_323	.470
76	convnext_xlarge:fb_in22k_ft_in1k	.469
77	ReAlnet09_ALL	.469
78	convnext_tiny:in12k_ft_in1k	.469
79	ReAlnet06_ALL	.469
80	vonegrcnn_47e	.469
81	convnext_base_imagenet_full_seed-0	.469
82	mobilenet_v2_1.0_128-tf	.469
83	ReAlnet05_cornet	.469
84	resnet18-local_aggregation	.469
85	convnext_base:clip_laiona_augreg_ft_in1k_384	.469
86	voneresnet-50	.469
87	antialiased-r50	.468
88	densenet-169-keras	.468
89	efficientnet_b0	.468
90	resnet50_ewconplus_wzc_seed2_2__323	.468
91	resnet-101_v2-tf	.468
92	ReAlnet04_ALL	.468
93	ReAlnet03_ALL	.468
94	vonegrcnn_47e	.468
95	resnet50-SIN_IN_IN	.468
96	voneresnet-50-robust	.468
97	densenet-169	.468
98	mobilenet_v2_0.5_192-tf	.468
99	ReAlnet02_ALL	.468
100	ReAlnet10_ALL	.468
101	resnet-18-LC_w_sh_1_iter_m	.468
102	ReAlnet01_ALL	.467
103	0.5x_resnet-18_LC_w_sh_10_iter	.467
104	mobilenet_v2_0.75_128	.467
105	grcnn	.467
106	ReAlnet05_ALL	.467
107	mobilenet_v2_0.75_192-tf	.467
108	resnet_SIN_IN_FT_IN	.467
109	mobilenet_v2_0.35_192	.467
110	ReAlnet08_ALL	.467
111	nasnet_mobile-tf	.467
112	convnext_tiny_sup	.467
113	mobilenet_v2_1_0_160	.466
114	mobilenet_v2_1-4_224_pytorch	.466
115	resnet-18-LC_w_sh_100_iter_m	.466
116	resnet50_ecoset_full	.466
117	convnext_large_imagenet_full_seed-0	.466
118	resnet-50_v2-tf	.466
119	resnet50_ewconplus_wzc_seed4_2_323	.466
120	ReAlnet07_ALL	.465
121	resnet152_ecoset_full	.465
122	mobilenet_v2_1_0_192	.465
123	mobilenet_v2_1_4_224	.465
124	resnet_50_v1_spiking	.465
125	resnet_50_v1	.465
126	resnet50-sup	.465
127	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.465
128	mobilenet_v2_1_0_224	.465
129	voneresnet-50-non_stochastic	.465
130	mobilenet_v2_0.5_160	.464
131	CORnet-S	.464
132	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.464
133	mobilenet_v2_0.5_224-tf	.464
134	mobilenet_v2_1.0_224-tf	.464
135	mobilenet_v1_0.75_192	.464
136	mobilenet_v1_1.0_192	.463
137	resnet50_imagenet_100_seed-0	.463
138	resnet50_random_linf8_perturb	.463
139	shufflenet_v2_x1_0	.463
140	mobilenet_v1_1.0_160	.463
141	resnet-152_v2-tf	.462
142	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.462
143	resnet101_imagenet_full	.462
144	nasnet_large-tf	.462
145	mobilenet_v1_1.0_224	.461
146	grcnn_robust_v1	.461
147	mobilenet_v1_1.0_128	.461
148	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.460
149	densenet-121-keras	.460
150	resnet50_st_wzc_2	.460
151	convnext_large:fb_in22k_ft_in1k	.460
152	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.459
153	resnet34_ecoset_full	.459
154	mobilenet_v2_1_3_224	.459
155	densenet-121	.459
156	BiT-M-R50x3	.459
157	resnet152_imagenet_full	.459
158	resnet50-vitoimagevidnet8	.459
159	resnet50_st_wzc_seed4_2_323	.458
160	mobilenet_v1_0.75_160	.458
161	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.458
162	BiT-M-R50x1	.458
163	inception_v2-tf	.458
164	resnet50_st_wzc_seed7_2_323	.458
165	resnet_50_v1_spiking_l4	.458
166	resnet_50_v1_spiking_l4a	.458
167	resnet50_tutorial	.458
168	yudixie_resnet50_imagenet1kpret_0_240908	.458
169	yudixie_resnet50_imagenet1kpret_0_240312	.458
170	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.457
171	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.457
172	BiT-S-R50x3	.457
173	grcnn_109	.457
174	mobilenet_v2_0_75_192	.457
175	mobilenet_v2_1_0_128	.457
176	Res2Net50_26w_4s	.457
177	mobilenet_v2_0_5_192	.457
178	resnet50_st_wzc_noseed_2_323	.457
179	mobilenet_v2_0_75_160	.457
180	resnet18-supervised	.456
181	mobilenet_v2_0.35_160	.456
182	antialias-resnet152	.456
183	resnet50_st_wzc_seed6_2_323	.456
184	mobilenet_v2_0_75_224	.456
185	resnet50_linf_4_robust	.455
186	resnet50	.455
187	mobilenet_v2_0.5_128	.455
188	resnet50_st_wzc_2_323	.455
189	vit_large_patch14_clip_224:openai_ft_in1k	.455
190	resnet50_random_l2_perturb	.455
191	resnet50_moco_v2	.454
192	mobilenet_v2_0.35_224	.454
193	deit_large_imagenet_full_seed-0	.454
194	inception_v1-tf	.454
195	CLIP-RN50	.454
196	inception_v3-tf	.453
197	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.453
198	mobilenet_v1_0.75_224	.453
199	resnet50_l2_3_robust	.453
200	cv_18_dagger_408_pretrained	.453
201	deit_base_imagenet_full_seed-0	.453
202	resnet50_st_wzc_seed5_2_323	.453
203	ReAlnet01_cornet_fov12	.453
204	focalnet_tiny_lrf_in1k	.453
205	yudixie_resnet18_imagenet1kpret_0_240719	.453
206	yudixie_wbh_object_class_scaling_0415_imagenet	.453
207	mobilenet_v1_0.75_128	.452
208	resnet101	.452
209	resnet34_imagenet_full	.452
210	BiT-S-R50x1	.452
211	grcnn_v2_text_noise	.452
212	regnet_y_400mf	.452
213	inception_v3	.452
214	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.452
215	resnet50_robust_l2_eps3	.451
216	BiT-S-R152x4	.451
217	convnext_femto_ols:d1_in1k	.451
218	compact_resnet50_robust_IT	.450
219	inception_resnet_v2	.450
220	resnet50_st_wzc_seed3_2_323	.450
221	resnet18_ecoset_full	.450
222	vit_large_patch14_clip_224:laion2b_ft_in1k	.449
223	resnet18_imagenet_full	.449
224	cvt_cvt-13-224-in1k_4_LucyV4	.449
225	omnivore_swinS	.449
226	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.449
227	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.448
228	resnext101_32x8d_wsl	.448
229	RN50	.448
230	omnivore_swinB	.448
231	ReAlnet01_cornet_fov4	.448
232	texture_shape_resnet50_trained_on_SIN	.447
233	compact_resnet50_IT	.447
234	0.5x_resnet-18	.446
235	resnet-18_test_m	.446
236	resnet-18	.446
237	vgg-16-keras	.446
238	inception_v1	.446
239	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.446
240	resnet18_imagenet21kP	.445
241	BiT-M-R101x3	.445
242	BiT-M-R152x4	.444
243	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.444
244	cvt_cvt-21-224-in1k_4_LucyV4	.444
245	resnet18-contrastive_multiview	.444
246	vgg_16	.443
247	ViT-B/32	.443
248	omnivore_swinT	.443
249	resnet-18-LC_1st_conv_m	.443
250	inception_v4-tf	.442
251	SWSL_resnet50	.442
252	vit_large_patch14_clip_336:laion2b_ft_in1k	.442
253	resnet50-VITO-8deg-cc	.442
254	cvt_cvt-13-384-in1k_4_LucyV4	.442
255	resnet18-deepcluster	.442
256	compact_vgg19_IT	.441
257	CLIP_ViT-B_32	.441
258	resnet50_simclr	.441
259	mobilenet_v1_0.5_192	.441
260	mobilenet_v2_1.0_96	.441
261	xception-keras	.441
262	resnet-18-LC_d_w_sh_1x1_conv_init_m	.441
263	CLIP_resnet50_float32	.441
264	CLIP_resnet50	.441
265	resnet-50-pytorch	.440
266	resnet-50-robust	.440
267	vit_base_patch16_clip_224:openai_ft_in1k	.440
268	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.440
269	deit3_base_patch16_224_fb_in1k	.440
270	compact_cornets_IT	.440
271	alexnet_random_l2_3_perturb	.440
272	mobilenet_v1_0.5_224	.440
273	resnet-34	.438
274	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.438
275	squeezenet1_1	.438
276	vgg-19-keras	.438
277	mobilenet_v2_0.75_96	.437
278	pnasnet_large-tf	.437
279	yudixie_resnet50_object_class_0_240908	.436
280	mobilenet_v1_0.5_128	.436
281	deit_small_imagenet_full_seed-0	.436
282	BiT-M-R152x2	.436
283	resnext101_32x48d_wsl	.436
284	0.5x_resnet-18_LC_w_sh_100_iter	.436
285	BiT-S-R101x3	.435
286	RN50	.435
287	resnet_101_v2	.435
288	CORnet-Z	.435
289	cvt_cvt-21-384-in1k_4_LucyV4	.435
290	mobilenet_v2_0_5_224	.434
291	convnext_small_imagenet_100_seed-0	.434
292	mobilenet_v1_0.5_160	.434
293	deit3_base_patch16_224_fb_in22k_ft_in1k	.434
294	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.434
295	resnext101_32x32d_wsl	.434
296	yudixie_resnet50_category_class_0_240908	.433
297	resnet_50_v2	.433
298	ViT_L_32_imagenet1k	.432
299	resnext101_32x16d_wsl	.432
300	alexnet	.430
301	alexnet_ks_torevert	.430
302	pnasnet_large_halfPrecision	.430
303	vision_transformer_vit_large_patch16_224	.430
304	BiT-M-R101x1	.430
305	imagenet_l2_3_0	.430
306	BiT-S-R152x2	.429
307	alexnet_random_linf8_perturb	.429
308	resnet50_byol	.429
309	ReAlnet10	.428
310	mobilenet_v2_0.35_128	.428
311	mobilenet_v1_0.25_224	.428
312	SWSL_resnext101_32x8d	.427
313	ReAlnet02	.427
314	ReAlnet01	.426
315	ReAlnet07	.426
316	ReAlnet06	.425
317	alexnet_fov4	.425
318	ReAlnet08	.425
319	ReAlnet04	.425
320	ReAlnet03	.424
321	mobilenet_v1_0.25_192	.424
322	ReAlnet09	.424
323	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.424
324	resnet50_linf_8_robust	.423
325	ReAlnet05	.422
326	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.422
327	BiT-S-R101x1	.422
328	mobilenet_v1_0.25_160	.422
329	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.422
330	alexnet_l2_3_robust	.422
331	convnext_base_fb_in1k_gram_aligned_dinov3	.421
332	VOneCORnet-S	.421
333	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.421
334	mobilenet_v2_0.5_96	.421
335	ReAlnet01_cornet_fov16	.421
336	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.420
337	alexnet_reduced_aliasing_early_checkpoint	.420
338	fixres_resnext101_32x48d_wsl	.419
339	vit_base_patch14_dinov2-lvd142m	.418
340	AlexNet_SIN	.416
341	cornet_s	.416
342	yudixie_resnet18_object_class_0_240719	.415
343	FrankRobWobv0	.415
344	yudixie_resnet18_category_class_0_240719	.415
345	vgg_19	.415
346	yudixie_resnet50_distance_translation_rotation_0_240908	.414
347	resnet_50_v1_spiking_l3	.413
348	resnet-18-LC_m	.413
349	yolos_tiny	.412
350	blt_vs	.412
351	yudixie_resnet50_translation_rotation_0_240908	.411
352	yudixie_resnet50_distance_translation_0_240908	.409
353	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.408
354	0.5x_resnet-18_LC	.408
355	resnet-18-LC_conv_init_m	.408
356	vit_base_patch16_dinov3-lvd1689m	.407
357	mobilenet_v2_0.35_96	.407
358	mobilenet_v1_0.25_128	.405
359	resnet18-colorization	.405
360	squeezenet1_0	.403
361	AlexNet_SIN_fov4	.403
362	alexnet_robust_correct	.402
363	alexnet_early_checkpoint	.400
364	alexnet_fov12	.400
365	texture_shape_alexnet_trained_on_SIN	.400
366	vonealexnet_gaussian_noise_std4_fixed	.397
367	deepeisnn_ei_imagenet_resnet18	.395
368	yudixie_resnet50_distance_reg_0_240908	.392
369	imagenet_l2_10_0	.390
370	resnet18-relative_position	.389
371	resnet-152_v2_pytorch	.389
372	yudixie_resnet50_rotation_reg_0_240908	.388
373	yudixie_resnet50_translation_reg_0_240908	.384
374	convnext_base_fb_in22k_ft_in1k	.382
375	AlexNet_SIN_fov12	.379
376	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.378
377	yudixie_resnet18_translation_rotation_0_240719	.377
378	resnet18-contrastive_predictive	.376
379	alexnet_fov16	.375
380	alexnet_linf_8_robust	.374
381	yudixie_resnet18_distance_translation_rotation_0_240719	.369
382	yudixie_resnet18_rotation_reg_0_240719	.366
383	yudixie_resnet18_distance_rotation_0_240719	.366
384	vggface	.364
385	yudixie_resnet50_distance_rotation_0_240908	.363
386	yudixie_resnet18_translation_reg_0_240719	.362
387	yudixie_resnet18_distance_translation_0_240719	.359
388	convnext_base_fb_in1k	.359
389	AlexNet_SIN_fov16	.355
390	resnet18-depth_prediction	.354
391	deit_small_imagenet_100_seed-0	.349
392	yudixie_resnet18_distance_reg_0_240719	.349
393	r3m_resnet34	.347
394	briaai_rmbg_1_4	.345
395	r3m_resnet18	.341
396	r3m_resnet50	.339
397	resnet18_fair	.335
398	artResNet18_1	.330
399	resnet50	.330
400	r3m_resnet50_nocrop	.325
401	resnet50-cifar	.311
402	resnet50_primary_visual_cortex	.308
403	prednet	.305
404	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.304
405	my-model	.300
406	deepeisnn_ei_cifar10_resnet18	.300
407	predictive_coding_pc	.299
408	deepeisnn_ei_cifar10_vgg19	.289
409	pr1_stl10_disentangled_alpha04	.288
410	resnet50_imagenet_10_seed-0	.285
411	CORnetZ_CIFAR10	.274
412	compact_resnet50_V4	.268
413	compact_resnet50_robust_V4	.266
414	aughost_fair_resnet18	.265
415	alexnet_training_seed_08	.257
416	v1-pyr-nodown	.256
417	alexnet_training_seed_03	.256
418	compact_vgg19_V4	.255
419	alexnet_training_seed_01	.254
420	alexnet_training_seed_02	.253
421	alexnet_training_seed_05	.253
422	alexnet_training_seed_04	.250
423	alexnet_training_seed_07	.250
424	alexnet_training_seed_09	.248
425	alexnet_training_seed_06	.245
426	alexnet_training_seed_10	.245
427	alexnet_training_seed_01_fov12	.245
428	resnet50_FractalDB	.243
429	mobilevit_small	.240
430	CORnetZ_CIFAR10_bs32_20_04	.239
431	resnet18-autoencoder	.239
432	alexnet_training_seed_01_fov4	.239
433	compact_cornets_V4	.238
434	alexnet_training_seed_01_fov16	.238
435	yudixie_wbh_object_class_scaling_0415_run_2	.226
436	yudixie_wbh_object_class_scaling_0415_run_3	.201
437	yudixie_wbh_object_class_scaling_0415_run_0	.198
438	resnet50_imagenet_1_seed-0	.195
439	yudixie_wbh_object_class_scaling_0415_run_1	.194
440	resnet-18_untrained	.194
441	yudixie_resnet18_random_0_240719	.192
442	resnet-50x2_untrained	.192
443	resnet50-meshes-lt-100-original-pretrained	.189
444	resnet50-meshes-lt-100-original-scratch	.189
445	resnet-50_untrained	.186
446	convnext_small_imagenet_10_seed-0	.181
447	yudixie_resnet50_random_0_240908	.174
448	resnet50_pretrained_with_retinal_waves	.159
449	resnet-18-LC_untrained	.155
450	fitvid_trained_on_physion	.144
451	deit_small_imagenet_10_seed-0	.103
452	deit_small_imagenet_1_seed-0	.083
453	convnext_small_imagenet_1_seed-0	.081
454	pixels	.062
455	my-model	.062
456	vit_base_patch14_reg4_dinov2-lvd142m

Benchmark bibtex

@misc{Sanghavi_DiCarlo_2021,
  title={Sanghavi2020},
  url={osf.io/chwdk},
  DOI={10.17605/OSF.IO/CHWDK},
  publisher={OSF},
  author={Sanghavi, Sachi and DiCarlo, James J},
  year={2021},
  month={Nov}
}

Ceiling

0.87.

Note that scores are relative to this ceiling.

Data: Sanghavi2020.IT

5760 stimuli recordings from 88 sites in IT

Metric: pls