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	.563
2	resnet50-barlow	.563
3	resnet50-vicregl0p9	.562
4	AdvProp_efficientnet-b7	.562
5	barlow-twins-resnet50	.561
6	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.560
7	AT_efficientnet-b7	.560
8	vonegrcnn_52e_full	.559
9	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.558
10	custom_model_cv_18_dagger_408	.556
11	vonegrcnn_62e_nobn	.556
12	AT_efficientnet-b2	.556
13	AdvProp_efficientnet-b4	.556
14	resnet50-vicregl0p75	.556
15	AT_efficientnet-b4	.555
16	AdvProp_efficientnet-b6	.555
17	AdvProp_efficientnet-b2	.555
18	AdvProp_efficientnet-b8	.554
19	konkle_alexnetgn_ipcl_ref01_primary_model	.553
20	efficientnet_b1_imagenet_full	.553
21	efficientnet_b2_imagenet_full	.553
22	AdvProp_efficientnet-b0	.553
23	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.553
24	efficientnet_b0_imagenet_full	.552
25	tv_efficientnet-b1	.552
26	resnet-18-LC_w_sh_10_iter_m	.551
27	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.551
28	convnext_tiny_imagenet_full_seed-0	.551
29	effnetv2m_custom384	.551
30	resnet-18-LC_w_sh_10_iter_conv_init_m	.550
31	0.5x_resnet-18_LC_w_sh_1_iter	.550
32	mobilenet_v2_1.0_192-tf	.549
33	resnet-152_v1-tf	.549
34	antialiased-rnext101_32x8d	.548
35	ReAlnet02_cornet	.548
36	resnet-101_v1-tf	.548
37	resnet-18-LC_w_sh_1_iter_conv_init_m	.548
38	resnet50-SIN_IN	.547
39	densenet-201-keras	.547
40	ReAlnet06_cornet	.546
41	efficientnet-b7	.546
42	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.546
43	mobilenet_v2_1.3_224-tf	.546
44	convnext_small_imagenet_full_seed-0	.545
45	mobilenet_v2_1.0_160-tf	.545
46	resnet50-moclr8deg	.545
47	mobilenet_v2_1.4_224-tf	.545
48	resnet-50_v1-tf	.545
49	ReAlnet03_cornet	.545
50	ReAlnet08_cornet	.545
51	ReAlnet04_cornet	.544
52	ReAlnet01_cornet	.544
53	resnet101_ecoset_full	.544
54	mobilenet_v2_0.75_224-tf	.543
55	ReAlnet07_cornet	.543
56	resnet50-simclr-vissl	.543
57	ReAlnet10_cornet	.543
58	resnet18-instance_recognition	.543
59	vit_relpos_base_patch16_clsgap_224:sw_in1k	.542
60	resnet50_robust_l2_eps1	.542
61	resnet50-SIN	.542
62	resnet-18-LC_w_sh_100_iter_conv_init_m	.542
63	effnetb1_272x240	.542
64	nasnet_mobile	.541
65	resnet50_imagenet_full	.541
66	mobilenet_v2_0.75_160-tf	.541
67	ReAlnet09_cornet	.541
68	convnext_xlarge:fb_in22k_ft_in1k	.541
69	convnext_tiny:in12k_ft_in1k	.540
70	vonegrcnn_47e	.540
71	convnext_base_imagenet_full_seed-0	.540
72	mobilenet_v2_1.0_128-tf	.540
73	ReAlnet05_cornet	.540
74	resnet18-local_aggregation	.540
75	convnext_base:clip_laiona_augreg_ft_in1k_384	.540
76	voneresnet-50	.540
77	antialiased-r50	.540
78	densenet-169-keras	.540
79	efficientnet_b0	.539
80	resnet-101_v2-tf	.539
81	vonegrcnn_47e	.539
82	resnet50-SIN_IN_IN	.539
83	voneresnet-50-robust	.539
84	densenet-169	.539
85	mobilenet_v2_0.5_192-tf	.539
86	resnet-18-LC_w_sh_1_iter_m	.539
87	0.5x_resnet-18_LC_w_sh_10_iter	.538
88	mobilenet_v2_0.75_128	.538
89	grcnn	.538
90	mobilenet_v2_0.75_192-tf	.538
91	resnet_SIN_IN_FT_IN	.538
92	mobilenet_v2_0.35_192	.538
93	nasnet_mobile-tf	.537
94	convnext_tiny_sup	.537
95	mobilenet_v2_1_0_160	.537
96	mobilenet_v2_1-4_224_pytorch	.537
97	resnet-18-LC_w_sh_100_iter_m	.537
98	resnet50_ecoset_full	.536
99	convnext_large_imagenet_full_seed-0	.536
100	resnet-50_v2-tf	.536
101	resnet152_ecoset_full	.536
102	mobilenet_v2_1_0_192	.536
103	mobilenet_v2_1_4_224	.536
104	resnet_50_v1	.536
105	resnet50-sup	.536
106	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.535
107	mobilenet_v2_1_0_224	.535
108	voneresnet-50-non_stochastic	.535
109	mobilenet_v2_0.5_160	.535
110	CORnet-S	.534
111	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.534
112	mobilenet_v2_0.5_224-tf	.534
113	mobilenet_v2_1.0_224-tf	.534
114	mobilenet_v1_0.75_192	.534
115	mobilenet_v1_1.0_192	.533
116	resnet50_imagenet_100_seed-0	.533
117	resnet50_random_linf8_perturb	.533
118	shufflenet_v2_x1_0	.533
119	mobilenet_v1_1.0_160	.533
120	resnet-152_v2-tf	.532
121	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.532
122	resnet101_imagenet_full	.532
123	nasnet_large-tf	.532
124	mobilenet_v1_1.0_224	.531
125	grcnn_robust_v1	.531
126	mobilenet_v1_1.0_128	.531
127	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.530
128	densenet-121-keras	.530
129	convnext_large:fb_in22k_ft_in1k	.529
130	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.529
131	resnet34_ecoset_full	.529
132	mobilenet_v2_1_3_224	.529
133	densenet-121	.529
134	BiT-M-R50x3	.528
135	resnet152_imagenet_full	.528
136	resnet50-vitoimagevidnet8	.528
137	mobilenet_v1_0.75_160	.528
138	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.528
139	BiT-M-R50x1	.528
140	inception_v2-tf	.527
141	resnet50_tutorial	.527
142	yudixie_resnet50_imagenet1kpret_0_240908	.527
143	yudixie_resnet50_imagenet1kpret_0_240312	.527
144	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.527
145	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.527
146	BiT-S-R50x3	.527
147	grcnn_109	.527
148	mobilenet_v2_0_75_192	.527
149	mobilenet_v2_1_0_128	.526
150	Res2Net50_26w_4s	.526
151	mobilenet_v2_0_5_192	.526
152	mobilenet_v2_0_75_160	.526
153	resnet18-supervised	.526
154	mobilenet_v2_0.35_160	.525
155	antialias-resnet152	.525
156	mobilenet_v2_0_75_224	.525
157	resnet50_linf_4_robust	.524
158	resnet50	.524
159	mobilenet_v2_0.5_128	.524
160	vit_large_patch14_clip_224:openai_ft_in1k	.524
161	resnet50_random_l2_perturb	.524
162	resnet50_moco_v2	.523
163	mobilenet_v2_0.35_224	.523
164	deit_large_imagenet_full_seed-0	.523
165	inception_v1-tf	.523
166	CLIP-RN50	.522
167	inception_v3-tf	.522
168	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.522
169	mobilenet_v1_0.75_224	.522
170	resnet50_l2_3_robust	.522
171	cv_18_dagger_408_pretrained	.522
172	deit_base_imagenet_full_seed-0	.522
173	focalnet_tiny_lrf_in1k	.521
174	yudixie_resnet18_imagenet1kpret_0_240719	.521
175	mobilenet_v1_0.75_128	.521
176	resnet101	.521
177	resnet34_imagenet_full	.521
178	BiT-S-R50x1	.521
179	grcnn_v2_text_noise	.520
180	regnet_y_400mf	.520
181	inception_v3	.520
182	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.520
183	resnet50_robust_l2_eps3	.520
184	BiT-S-R152x4	.519
185	convnext_femto_ols:d1_in1k	.519
186	inception_resnet_v2	.518
187	resnet18_ecoset_full	.518
188	vit_large_patch14_clip_224:laion2b_ft_in1k	.517
189	resnet18_imagenet_full	.517
190	cvt_cvt-13-224-in1k_4_LucyV4	.517
191	omnivore_swinS	.517
192	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.517
193	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.516
194	resnext101_32x8d_wsl	.516
195	RN50	.516
196	omnivore_swinB	.516
197	texture_shape_resnet50_trained_on_SIN	.515
198	0.5x_resnet-18	.514
199	resnet-18_test_m	.514
200	resnet-18	.514
201	vgg-16-keras	.514
202	inception_v1	.513
203	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.513
204	resnet18_imagenet21kP	.513
205	BiT-M-R101x3	.513
206	BiT-M-R152x4	.512
207	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.512
208	cvt_cvt-21-224-in1k_4_LucyV4	.512
209	resnet18-contrastive_multiview	.511
210	vgg_16	.511
211	ViT-B/32	.511
212	omnivore_swinT	.510
213	resnet-18-LC_1st_conv_m	.510
214	inception_v4-tf	.510
215	SWSL_resnet50	.509
216	vit_large_patch14_clip_336:laion2b_ft_in1k	.509
217	resnet50-VITO-8deg-cc	.509
218	cvt_cvt-13-384-in1k_4_LucyV4	.509
219	resnet18-deepcluster	.509
220	CLIP_ViT-B_32	.508
221	resnet50_simclr	.508
222	mobilenet_v1_0.5_192	.508
223	mobilenet_v2_1.0_96	.508
224	xception-keras	.508
225	resnet-18-LC_d_w_sh_1x1_conv_init_m	.508
226	CLIP_resnet50_float32	.507
227	CLIP_resnet50	.507
228	resnet-50-pytorch	.507
229	resnet-50-robust	.507
230	vit_base_patch16_clip_224:openai_ft_in1k	.507
231	alexnet_random_l2_3_perturb	.506
232	mobilenet_v1_0.5_224	.506
233	resnet-34	.505
234	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.505
235	squeezenet1_1	.504
236	vgg-19-keras	.504
237	mobilenet_v2_0.75_96	.503
238	pnasnet_large-tf	.503
239	yudixie_resnet50_object_class_0_240908	.503
240	mobilenet_v1_0.5_128	.503
241	deit_small_imagenet_full_seed-0	.502
242	BiT-M-R152x2	.502
243	resnext101_32x48d_wsl	.502
244	0.5x_resnet-18_LC_w_sh_100_iter	.502
245	BiT-S-R101x3	.502
246	RN50	.501
247	resnet_101_v2	.501
248	CORnet-Z	.501
249	cvt_cvt-21-384-in1k_4_LucyV4	.501
250	mobilenet_v2_0_5_224	.500
251	convnext_small_imagenet_100_seed-0	.500
252	mobilenet_v1_0.5_160	.500
253	resnext101_32x32d_wsl	.500
254	yudixie_resnet50_category_class_0_240908	.499
255	resnet_50_v2	.498
256	ViT_L_32_imagenet1k	.497
257	resnext101_32x16d_wsl	.497
258	alexnet	.496
259	alexnet	.496
260	alexnet	.496
261	alexnet	.496
262	alexnet	.496
263	alexnet	.496
264	alexnet-baseline	.496
265	alexnet	.496
266	alexnet	.496
267	alexnet_ks_torevert	.496
268	vision_transformer_vit_large_patch16_224	.495
269	BiT-M-R101x1	.495
270	imagenet_l2_3_0	.495
271	BiT-S-R152x2	.494
272	alexnet_random_linf8_perturb	.494
273	resnet50_byol	.494
274	ReAlnet10	.493
275	mobilenet_v2_0.35_128	.493
276	mobilenet_v1_0.25_224	.493
277	SWSL_resnext101_32x8d	.492
278	ReAlnet02	.492
279	ReAlnet_incorrect	.491
280	ReAlnet01	.491
281	ReAlnet07	.491
282	ReAlnet06	.490
283	ReAlnet08	.490
284	ReAlnet04	.489
285	ReAlnet03	.489
286	mobilenet_v1_0.25_192	.489
287	ReAlnet09	.489
288	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.488
289	resnet50_linf_8_robust	.487
290	ReAlnet05	.486
291	BiT-S-R101x1	.486
292	mobilenet_v1_0.25_160	.486
293	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.486
294	alexnet_l2_3_robust	.486
295	alexnet	.485
296	VOneCORnet-S	.485
297	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.485
298	mobilenet_v2_0.5_96	.485
299	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.484
300	alexnet_reduced_aliasing_early_checkpoint	.483
301	fixres_resnext101_32x48d_wsl	.483
302	AlexNet_SIN	.479
303	cornet_s	.479
304	yudixie_resnet18_object_class_0_240719	.479
305	FrankRobWobv0	.478
306	yudixie_resnet18_category_class_0_240719	.477
307	vgg_19	.477
308	yudixie_resnet50_distance_translation_rotation_0_240908	.477
309	resnet-18-LC_m	.476
310	blt_vs	.475
311	yudixie_resnet50_translation_rotation_0_240908	.473
312	yudixie_resnet50_distance_translation_0_240908	.471
313	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.470
314	0.5x_resnet-18_LC	.470
315	resnet-18-LC_conv_init_m	.469
316	mobilenet_v2_0.35_96	.468
317	mobilenet_v1_0.25_128	.467
318	resnet18-colorization	.466
319	squeezenet1_0	.464
320	alexnet_robust_correct	.463
321	alexnet_early_checkpoint	.461
322	texture_shape_alexnet_trained_on_SIN	.461
323	vonealexnet_gaussian_noise_std4_fixed	.457
324	yudixie_resnet50_distance_reg_0_240908	.452
325	imagenet_l2_10_0	.449
326	resnet18-relative_position	.448
327	resnet-152_v2_pytorch	.448
328	yudixie_resnet50_rotation_reg_0_240908	.447
329	yudixie_resnet50_translation_reg_0_240908	.442
330	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.435
331	yudixie_resnet18_translation_rotation_0_240719	.434
332	resnet18-contrastive_predictive	.433
333	alexnet_linf_8_robust	.431
334	yudixie_resnet18_distance_translation_rotation_0_240719	.425
335	yudixie_resnet18_rotation_reg_0_240719	.422
336	yudixie_resnet18_distance_rotation_0_240719	.422
337	vggface	.419
338	yudixie_resnet50_distance_rotation_0_240908	.418
339	yudixie_resnet18_translation_reg_0_240719	.417
340	yudixie_resnet18_distance_translation_0_240719	.414
341	resnet18-depth_prediction	.408
342	deit_small_imagenet_100_seed-0	.402
343	yudixie_resnet18_distance_reg_0_240719	.402
344	r3m_resnet34	.400
345	r3m_resnet18	.393
346	r3m_resnet50	.391
347	artResNet18_1	.380
348	resnet50	.380
349	r3m_resnet50_nocrop	.375
350	resnet50-cifar	.359
351	prednet	.351
352	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.350
353	my-model	.346
354	resnet50_imagenet_10_seed-0	.329
355	CORnetZ_CIFAR10	.316
356	alexnet_training_seed_08	.296
357	v1-pyr-nodown	.295
358	alexnet_training_seed_03	.295
359	alexnet_training_seed_01	.293
360	alexnet_training_seed_02	.292
361	alexnet_training_seed_05	.291
362	alexnet_training_seed_04	.288
363	alexnet_training_seed_07	.288
364	alexnet_training_seed_09	.286
365	alexnet_training_seed_06	.282
366	alexnet_training_seed_10	.282
367	resnet50_FractalDB	.280
368	mobilevit_small	.276
369	CORnetZ_CIFAR10_bs32_20_04	.276
370	resnet18-autoencoder	.276
371	resnet50_imagenet_1_seed-0	.224
372	resnet-18_untrained	.223
373	yudixie_resnet18_random_0_240719	.221
374	resnet-50x2_untrained	.221
375	resnet50-meshes-lt-100-original-pretrained	.218
376	resnet50-meshes-lt-100-original-scratch	.217
377	resnet-50_untrained	.214
378	convnext_small_imagenet_10_seed-0	.208
379	yudixie_resnet50_random_0_240908	.201
380	resnet50_pretrained_with_retinal_waves	.183
381	resnet-18-LC_untrained	.179
382	fitvid_trained_on_physion	.166
383	deit_small_imagenet_10_seed-0	.118
384	deit_small_imagenet_1_seed-0	.095
385	convnext_small_imagenet_1_seed-0	.093
386	pixels	.072
387	my-model	.071
388	AT_efficientnet-b0	X
389	nasnet_large	X
390	densenet_201_pytorch	X
391	pnasnet_large_pytorch	X
392	pnasnet_large	X
393	inception_v3_pytorch	X
394	hmax	X
395	MIM	X
396	TAU	X
397	SimVP	X
398	PredRNN	X
399	ConvLSTM	X
400	densenet-201	X
401	resnet18-simclr	X
402	efficientnet-b4	X
403	efficientnet-b2	X
404	efficientnet-b6	X
405	efficientnet-b0	X
406	openclip	X
407	vonegrcnn_62e_nobn	X
408	inception_v4	X
409	resnet_101_v1	X
410	resnet_152_v2	X
411	vonegrcnn_52e_full	X
412	resnet50_ImageNet	X
413	resnet_152_v1	X
414	xception	X

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