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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	resnet50-vicreg	.489
2	resnet50-barlow	.489
3	resnet50-vicregl0p9	.488
4	AdvProp_efficientnet-b7	.488
5	barlow-twins-resnet50	.487
6	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.487
7	AT_efficientnet-b7	.486
8	vonegrcnn_52e_full	.485
9	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.485
10	custom_model_cv_18_dagger_408	.483
11	vonegrcnn_62e_nobn	.483
12	AT_efficientnet-b2	.483
13	AdvProp_efficientnet-b4	.483
14	resnet50-vicregl0p75	.483
15	AT_efficientnet-b4	.482
16	AdvProp_efficientnet-b6	.482
17	AdvProp_efficientnet-b2	.482
18	AdvProp_efficientnet-b8	.481
19	konkle_alexnetgn_ipcl_ref01_primary_model	.481
20	efficientnet_b1_imagenet_full	.480
21	efficientnet_b2_imagenet_full	.480
22	AdvProp_efficientnet-b0	.480
23	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.480
24	efficientnet_b0_imagenet_full	.479
25	tv_efficientnet-b1	.479
26	resnet-18-LC_w_sh_10_iter_m	.479
27	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.479
28	convnext_tiny_imagenet_full_seed-0	.479
29	effnetv2m_custom384	.478
30	resnet-18-LC_w_sh_10_iter_conv_init_m	.478
31	0.5x_resnet-18_LC_w_sh_1_iter	.478
32	mobilenet_v2_1.0_192-tf	.477
33	resnet-152_v1-tf	.477
34	antialiased-rnext101_32x8d	.476
35	ReAlnet02_cornet	.476
36	resnet-101_v1-tf	.476
37	resnet-18-LC_w_sh_1_iter_conv_init_m	.476
38	resnet50_ewconplus_wzc	.475
39	resnet50-SIN_IN	.475
40	densenet-201-keras	.475
41	ReAlnet06_cornet	.474
42	efficientnet-b7	.474
43	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.474
44	mobilenet_v2_1.3_224-tf	.474
45	convnext_small_imagenet_full_seed-0	.473
46	mobilenet_v2_1.0_160-tf	.473
47	resnet50-moclr8deg	.473
48	mobilenet_v2_1.4_224-tf	.473
49	resnet-50_v1-tf	.473
50	ReAlnet03_cornet	.473
51	ReAlnet08_cornet	.473
52	ReAlnet04_cornet	.473
53	ReAlnet01_cornet	.473
54	resnet101_ecoset_full	.473
55	mobilenet_v2_0.75_224-tf	.471
56	ReAlnet07_cornet	.471
57	resnet50-simclr-vissl	.471
58	ReAlnet10_cornet	.471
59	resnet18-instance_recognition	.471
60	vit_relpos_base_patch16_clsgap_224:sw_in1k	.471
61	resnet50_robust_l2_eps1	.471
62	resnet50-SIN	.471
63	resnet-18-LC_w_sh_100_iter_conv_init_m	.470
64	effnetb1_272x240	.470
65	nasnet_mobile	.470
66	resnet50_imagenet_full	.470
67	mobilenet_v2_0.75_160-tf	.470
68	ReAlnet09_cornet	.470
69	convnext_xlarge:fb_in22k_ft_in1k	.469
70	ReAlnet09_ALL	.469
71	convnext_tiny:in12k_ft_in1k	.469
72	ReAlnet06_ALL	.469
73	vonegrcnn_47e	.469
74	convnext_base_imagenet_full_seed-0	.469
75	mobilenet_v2_1.0_128-tf	.469
76	ReAlnet05_cornet	.469
77	resnet18-local_aggregation	.469
78	convnext_base:clip_laiona_augreg_ft_in1k_384	.469
79	voneresnet-50	.469
80	antialiased-r50	.468
81	densenet-169-keras	.468
82	efficientnet_b0	.468
83	resnet-101_v2-tf	.468
84	ReAlnet04_ALL	.468
85	ReAlnet03_ALL	.468
86	vonegrcnn_47e	.468
87	resnet50-SIN_IN_IN	.468
88	voneresnet-50-robust	.468
89	densenet-169	.468
90	mobilenet_v2_0.5_192-tf	.468
91	ReAlnet02_ALL	.468
92	ReAlnet10_ALL	.468
93	resnet-18-LC_w_sh_1_iter_m	.468
94	ReAlnet01_ALL	.467
95	0.5x_resnet-18_LC_w_sh_10_iter	.467
96	mobilenet_v2_0.75_128	.467
97	grcnn	.467
98	ReAlnet05_ALL	.467
99	mobilenet_v2_0.75_192-tf	.467
100	resnet_SIN_IN_FT_IN	.467
101	mobilenet_v2_0.35_192	.467
102	ReAlnet08_ALL	.467
103	nasnet_mobile-tf	.467
104	convnext_tiny_sup	.467
105	mobilenet_v2_1_0_160	.466
106	mobilenet_v2_1-4_224_pytorch	.466
107	resnet-18-LC_w_sh_100_iter_m	.466
108	resnet50_ecoset_full	.466
109	convnext_large_imagenet_full_seed-0	.466
110	resnet-50_v2-tf	.466
111	ReAlnet07_ALL	.465
112	resnet152_ecoset_full	.465
113	mobilenet_v2_1_0_192	.465
114	mobilenet_v2_1_4_224	.465
115	resnet_50_v1_spiking	.465
116	resnet_50_v1	.465
117	resnet50-sup	.465
118	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.465
119	mobilenet_v2_1_0_224	.465
120	voneresnet-50-non_stochastic	.465
121	mobilenet_v2_0.5_160	.464
122	CORnet-S	.464
123	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.464
124	mobilenet_v2_0.5_224-tf	.464
125	mobilenet_v2_1.0_224-tf	.464
126	mobilenet_v1_0.75_192	.464
127	mobilenet_v1_1.0_192	.463
128	resnet50_imagenet_100_seed-0	.463
129	resnet50_random_linf8_perturb	.463
130	shufflenet_v2_x1_0	.463
131	mobilenet_v1_1.0_160	.463
132	resnet-152_v2-tf	.462
133	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.462
134	resnet101_imagenet_full	.462
135	nasnet_large-tf	.462
136	mobilenet_v1_1.0_224	.461
137	grcnn_robust_v1	.461
138	mobilenet_v1_1.0_128	.461
139	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.460
140	densenet-121-keras	.460
141	convnext_large:fb_in22k_ft_in1k	.460
142	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.459
143	resnet34_ecoset_full	.459
144	mobilenet_v2_1_3_224	.459
145	densenet-121	.459
146	BiT-M-R50x3	.459
147	resnet152_imagenet_full	.459
148	resnet50-vitoimagevidnet8	.459
149	mobilenet_v1_0.75_160	.458
150	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.458
151	BiT-M-R50x1	.458
152	inception_v2-tf	.458
153	resnet_50_v1_spiking_l4	.458
154	resnet_50_v1_spiking_l4a	.458
155	resnet50_tutorial	.458
156	yudixie_resnet50_imagenet1kpret_0_240908	.458
157	yudixie_resnet50_imagenet1kpret_0_240312	.458
158	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.457
159	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.457
160	BiT-S-R50x3	.457
161	grcnn_109	.457
162	mobilenet_v2_0_75_192	.457
163	mobilenet_v2_1_0_128	.457
164	Res2Net50_26w_4s	.457
165	mobilenet_v2_0_5_192	.457
166	mobilenet_v2_0_75_160	.457
167	resnet18-supervised	.456
168	mobilenet_v2_0.35_160	.456
169	antialias-resnet152	.456
170	mobilenet_v2_0_75_224	.456
171	resnet50_linf_4_robust	.455
172	resnet50	.455
173	mobilenet_v2_0.5_128	.455
174	vit_large_patch14_clip_224:openai_ft_in1k	.455
175	resnet50_random_l2_perturb	.455
176	resnet50_moco_v2	.454
177	mobilenet_v2_0.35_224	.454
178	deit_large_imagenet_full_seed-0	.454
179	inception_v1-tf	.454
180	CLIP-RN50	.454
181	inception_v3-tf	.453
182	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.453
183	mobilenet_v1_0.75_224	.453
184	resnet50_l2_3_robust	.453
185	cv_18_dagger_408_pretrained	.453
186	deit_base_imagenet_full_seed-0	.453
187	ReAlnet01_cornet_fov12	.453
188	focalnet_tiny_lrf_in1k	.453
189	yudixie_resnet18_imagenet1kpret_0_240719	.453
190	mobilenet_v1_0.75_128	.452
191	resnet101	.452
192	resnet34_imagenet_full	.452
193	BiT-S-R50x1	.452
194	grcnn_v2_text_noise	.452
195	regnet_y_400mf	.452
196	inception_v3	.452
197	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.452
198	resnet50_robust_l2_eps3	.451
199	BiT-S-R152x4	.451
200	convnext_femto_ols:d1_in1k	.451
201	compact_resnet50_robust_IT	.450
202	inception_resnet_v2	.450
203	resnet18_ecoset_full	.450
204	vit_large_patch14_clip_224:laion2b_ft_in1k	.449
205	resnet18_imagenet_full	.449
206	cvt_cvt-13-224-in1k_4_LucyV4	.449
207	omnivore_swinS	.449
208	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.449
209	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.448
210	resnext101_32x8d_wsl	.448
211	RN50	.448
212	omnivore_swinB	.448
213	ReAlnet01_cornet_fov4	.448
214	texture_shape_resnet50_trained_on_SIN	.447
215	compact_resnet50_IT	.447
216	0.5x_resnet-18	.446
217	resnet-18_test_m	.446
218	resnet-18	.446
219	vgg-16-keras	.446
220	inception_v1	.446
221	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.446
222	resnet18_imagenet21kP	.445
223	BiT-M-R101x3	.445
224	BiT-M-R152x4	.444
225	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.444
226	cvt_cvt-21-224-in1k_4_LucyV4	.444
227	resnet18-contrastive_multiview	.444
228	vgg_16	.443
229	ViT-B/32	.443
230	omnivore_swinT	.443
231	resnet-18-LC_1st_conv_m	.443
232	inception_v4-tf	.442
233	SWSL_resnet50	.442
234	vit_large_patch14_clip_336:laion2b_ft_in1k	.442
235	resnet50-VITO-8deg-cc	.442
236	cvt_cvt-13-384-in1k_4_LucyV4	.442
237	resnet18-deepcluster	.442
238	compact_vgg19_IT	.441
239	CLIP_ViT-B_32	.441
240	resnet50_simclr	.441
241	mobilenet_v1_0.5_192	.441
242	mobilenet_v2_1.0_96	.441
243	xception-keras	.441
244	resnet-18-LC_d_w_sh_1x1_conv_init_m	.441
245	CLIP_resnet50_float32	.441
246	CLIP_resnet50	.441
247	resnet-50-pytorch	.440
248	resnet-50-robust	.440
249	vit_base_patch16_clip_224:openai_ft_in1k	.440
250	compact_cornets_IT	.440
251	alexnet_random_l2_3_perturb	.440
252	mobilenet_v1_0.5_224	.440
253	resnet-34	.438
254	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.438
255	squeezenet1_1	.438
256	vgg-19-keras	.438
257	mobilenet_v2_0.75_96	.437
258	pnasnet_large-tf	.437
259	yudixie_resnet50_object_class_0_240908	.436
260	mobilenet_v1_0.5_128	.436
261	deit_small_imagenet_full_seed-0	.436
262	BiT-M-R152x2	.436
263	resnext101_32x48d_wsl	.436
264	0.5x_resnet-18_LC_w_sh_100_iter	.436
265	BiT-S-R101x3	.435
266	RN50	.435
267	resnet_101_v2	.435
268	CORnet-Z	.435
269	cvt_cvt-21-384-in1k_4_LucyV4	.435
270	mobilenet_v2_0_5_224	.434
271	convnext_small_imagenet_100_seed-0	.434
272	mobilenet_v1_0.5_160	.434
273	resnext101_32x32d_wsl	.434
274	yudixie_resnet50_category_class_0_240908	.433
275	resnet_50_v2	.433
276	ViT_L_32_imagenet1k	.432
277	resnext101_32x16d_wsl	.432
278	alexnet	.430
279	alexnet	.430
280	alexnet	.430
281	alexnet	.430
282	alexnet	.430
283	alexnet	.430
284	alexnet_workflow_trigger	.430
285	alexnet	.430
286	alexnet-baseline	.430
287	alexnet	.430
288	alexnet	.430
289	alexnet_ks_torevert	.430
290	vision_transformer_vit_large_patch16_224	.430
291	BiT-M-R101x1	.430
292	imagenet_l2_3_0	.430
293	BiT-S-R152x2	.429
294	alexnet_random_linf8_perturb	.429
295	resnet50_byol	.429
296	ReAlnet10	.428
297	mobilenet_v2_0.35_128	.428
298	mobilenet_v1_0.25_224	.428
299	SWSL_resnext101_32x8d	.427
300	ReAlnet02	.427
301	ReAlnet01	.426
302	ReAlnet07	.426
303	ReAlnet06	.425
304	alexnet_fov4	.425
305	ReAlnet08	.425
306	ReAlnet04	.425
307	ReAlnet03	.424
308	mobilenet_v1_0.25_192	.424
309	ReAlnet09	.424
310	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.424
311	resnet50_linf_8_robust	.423
312	ReAlnet05	.422
313	BiT-S-R101x1	.422
314	mobilenet_v1_0.25_160	.422
315	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.422
316	alexnet_l2_3_robust	.422
317	alexnet	.421
318	VOneCORnet-S	.421
319	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.421
320	mobilenet_v2_0.5_96	.421
321	ReAlnet01_cornet_fov16	.421
322	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.420
323	alexnet_reduced_aliasing_early_checkpoint	.420
324	fixres_resnext101_32x48d_wsl	.419
325	AlexNet_SIN	.416
326	cornet_s	.416
327	yudixie_resnet18_object_class_0_240719	.415
328	FrankRobWobv0	.415
329	yudixie_resnet18_category_class_0_240719	.415
330	vgg_19	.415
331	yudixie_resnet50_distance_translation_rotation_0_240908	.414
332	resnet_50_v1_spiking_l3	.413
333	resnet-18-LC_m	.413
334	yolos_tiny	.412
335	blt_vs	.412
336	yudixie_resnet50_translation_rotation_0_240908	.411
337	yudixie_resnet50_distance_translation_0_240908	.409
338	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.408
339	0.5x_resnet-18_LC	.408
340	resnet-18-LC_conv_init_m	.408
341	vit_base_patch16_dinov3:lvd1689m	.407
342	mobilenet_v2_0.35_96	.407
343	mobilenet_v1_0.25_128	.405
344	resnet18-colorization	.405
345	squeezenet1_0	.403
346	AlexNet_SIN_fov4	.403
347	alexnet_robust_correct	.402
348	alexnet_early_checkpoint	.400
349	alexnet_fov12	.400
350	texture_shape_alexnet_trained_on_SIN	.400
351	vonealexnet_gaussian_noise_std4_fixed	.397
352	vit_base_patch14_reg4_dinov2:lvd142m	.396
353	yudixie_resnet50_distance_reg_0_240908	.392
354	imagenet_l2_10_0	.390
355	resnet18-relative_position	.389
356	resnet-152_v2_pytorch	.389
357	yudixie_resnet50_rotation_reg_0_240908	.388
358	yudixie_resnet50_translation_reg_0_240908	.384
359	AlexNet_SIN_fov12	.379
360	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.378
361	yudixie_resnet18_translation_rotation_0_240719	.377
362	resnet18-contrastive_predictive	.376
363	alexnet_fov16	.375
364	alexnet_linf_8_robust	.374
365	yudixie_resnet18_distance_translation_rotation_0_240719	.369
366	yudixie_resnet18_rotation_reg_0_240719	.366
367	yudixie_resnet18_distance_rotation_0_240719	.366
368	vggface	.364
369	yudixie_resnet50_distance_rotation_0_240908	.363
370	yudixie_resnet18_translation_reg_0_240719	.362
371	yudixie_resnet18_distance_translation_0_240719	.359
372	AlexNet_SIN_fov16	.355
373	resnet18-depth_prediction	.354
374	deit_small_imagenet_100_seed-0	.349
375	yudixie_resnet18_distance_reg_0_240719	.349
376	r3m_resnet34	.347
377	briaai_rmbg_1_4	.345
378	r3m_resnet18	.341
379	r3m_resnet50	.339
380	artResNet18_1	.330
381	resnet50	.330
382	r3m_resnet50_nocrop	.325
383	resnet50-cifar	.311
384	resnet50_primary_visual_cortex	.308
385	prednet	.305
386	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.304
387	my-model	.300
388	resnet50_imagenet_10_seed-0	.285
389	CORnetZ_CIFAR10	.274
390	compact_resnet50_V4	.268
391	compact_resnet50_robust_V4	.266
392	alexnet_training_seed_08	.257
393	v1-pyr-nodown	.256
394	alexnet_training_seed_03	.256
395	compact_vgg19_V4	.255
396	alexnet_training_seed_01	.254
397	alexnet_training_seed_02	.253
398	alexnet_training_seed_05	.253
399	alexnet_training_seed_04	.250
400	alexnet_training_seed_07	.250
401	alexnet_training_seed_09	.248
402	alexnet_training_seed_06	.245
403	alexnet_training_seed_10	.245
404	alexnet_training_seed_01_fov12	.245
405	resnet50_FractalDB	.243
406	mobilevit_small	.240
407	CORnetZ_CIFAR10_bs32_20_04	.239
408	resnet18-autoencoder	.239
409	alexnet_training_seed_01_fov4	.239
410	compact_cornets_V4	.238
411	alexnet_training_seed_01_fov16	.238
412	resnet50_imagenet_1_seed-0	.195
413	resnet-18_untrained	.194
414	yudixie_resnet18_random_0_240719	.192
415	resnet-50x2_untrained	.192
416	resnet50-meshes-lt-100-original-pretrained	.189
417	resnet50-meshes-lt-100-original-scratch	.189
418	resnet-50_untrained	.186
419	convnext_small_imagenet_10_seed-0	.181
420	yudixie_resnet50_random_0_240908	.174
421	resnet50_pretrained_with_retinal_waves	.159
422	resnet-18-LC_untrained	.155
423	fitvid_trained_on_physion	.144
424	deit_small_imagenet_10_seed-0	.103
425	deit_small_imagenet_1_seed-0	.083
426	convnext_small_imagenet_1_seed-0	.081
427	pixels	.062
428	my-model	.062
429	vit_base_patch14_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