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_spiking	.536
105	resnet_50_v1	.536
106	resnet50-sup	.536
107	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.535
108	mobilenet_v2_1_0_224	.535
109	voneresnet-50-non_stochastic	.535
110	mobilenet_v2_0.5_160	.535
111	CORnet-S	.534
112	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.534
113	mobilenet_v2_0.5_224-tf	.534
114	mobilenet_v2_1.0_224-tf	.534
115	mobilenet_v1_0.75_192	.534
116	mobilenet_v1_1.0_192	.533
117	resnet50_imagenet_100_seed-0	.533
118	resnet50_random_linf8_perturb	.533
119	shufflenet_v2_x1_0	.533
120	mobilenet_v1_1.0_160	.533
121	resnet-152_v2-tf	.532
122	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.532
123	resnet101_imagenet_full	.532
124	nasnet_large-tf	.532
125	mobilenet_v1_1.0_224	.531
126	grcnn_robust_v1	.531
127	mobilenet_v1_1.0_128	.531
128	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.530
129	densenet-121-keras	.530
130	convnext_large:fb_in22k_ft_in1k	.529
131	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.529
132	resnet34_ecoset_full	.529
133	mobilenet_v2_1_3_224	.529
134	densenet-121	.529
135	BiT-M-R50x3	.528
136	resnet152_imagenet_full	.528
137	resnet50-vitoimagevidnet8	.528
138	mobilenet_v1_0.75_160	.528
139	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.528
140	BiT-M-R50x1	.528
141	inception_v2-tf	.527
142	resnet50_tutorial	.527
143	resnet_50_v1_spiking_l4	.527
144	resnet_50_v1_spiking_l4a	.527
145	yudixie_resnet50_imagenet1kpret_0_240908	.527
146	yudixie_resnet50_imagenet1kpret_0_240312	.527
147	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.527
148	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.527
149	BiT-S-R50x3	.527
150	grcnn_109	.527
151	mobilenet_v2_0_75_192	.527
152	mobilenet_v2_1_0_128	.526
153	Res2Net50_26w_4s	.526
154	mobilenet_v2_0_5_192	.526
155	mobilenet_v2_0_75_160	.526
156	resnet18-supervised	.526
157	mobilenet_v2_0.35_160	.525
158	antialias-resnet152	.525
159	mobilenet_v2_0_75_224	.525
160	resnet50_linf_4_robust	.524
161	resnet50	.524
162	mobilenet_v2_0.5_128	.524
163	vit_large_patch14_clip_224:openai_ft_in1k	.524
164	resnet50_random_l2_perturb	.524
165	resnet50_moco_v2	.523
166	mobilenet_v2_0.35_224	.523
167	deit_large_imagenet_full_seed-0	.523
168	inception_v1-tf	.523
169	CLIP-RN50	.522
170	inception_v3-tf	.522
171	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.522
172	mobilenet_v1_0.75_224	.522
173	resnet50_l2_3_robust	.522
174	cv_18_dagger_408_pretrained	.522
175	deit_base_imagenet_full_seed-0	.522
176	focalnet_tiny_lrf_in1k	.521
177	yudixie_resnet18_imagenet1kpret_0_240719	.521
178	mobilenet_v1_0.75_128	.521
179	resnet101	.521
180	resnet34_imagenet_full	.521
181	BiT-S-R50x1	.521
182	grcnn_v2_text_noise	.520
183	regnet_y_400mf	.520
184	inception_v3	.520
185	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.520
186	resnet50_robust_l2_eps3	.520
187	BiT-S-R152x4	.519
188	convnext_femto_ols:d1_in1k	.519
189	inception_resnet_v2	.518
190	resnet18_ecoset_full	.518
191	vit_large_patch14_clip_224:laion2b_ft_in1k	.517
192	resnet18_imagenet_full	.517
193	cvt_cvt-13-224-in1k_4_LucyV4	.517
194	omnivore_swinS	.517
195	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.517
196	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.516
197	resnext101_32x8d_wsl	.516
198	RN50	.516
199	omnivore_swinB	.516
200	texture_shape_resnet50_trained_on_SIN	.515
201	0.5x_resnet-18	.514
202	resnet-18_test_m	.514
203	resnet-18	.514
204	vgg-16-keras	.514
205	inception_v1	.513
206	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.513
207	resnet18_imagenet21kP	.513
208	BiT-M-R101x3	.513
209	BiT-M-R152x4	.512
210	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.512
211	cvt_cvt-21-224-in1k_4_LucyV4	.512
212	resnet18-contrastive_multiview	.511
213	vgg_16	.511
214	ViT-B/32	.511
215	omnivore_swinT	.510
216	resnet-18-LC_1st_conv_m	.510
217	inception_v4-tf	.510
218	SWSL_resnet50	.509
219	vit_large_patch14_clip_336:laion2b_ft_in1k	.509
220	resnet50-VITO-8deg-cc	.509
221	cvt_cvt-13-384-in1k_4_LucyV4	.509
222	resnet18-deepcluster	.509
223	CLIP_ViT-B_32	.508
224	resnet50_simclr	.508
225	mobilenet_v1_0.5_192	.508
226	mobilenet_v2_1.0_96	.508
227	xception-keras	.508
228	resnet-18-LC_d_w_sh_1x1_conv_init_m	.508
229	CLIP_resnet50_float32	.507
230	CLIP_resnet50	.507
231	resnet-50-robust	.507
232	resnet-50-pytorch	.507
233	vit_base_patch16_clip_224:openai_ft_in1k	.507
234	alexnet_random_l2_3_perturb	.506
235	mobilenet_v1_0.5_224	.506
236	resnet-34	.505
237	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.505
238	squeezenet1_1	.504
239	vgg-19-keras	.504
240	mobilenet_v2_0.75_96	.503
241	pnasnet_large-tf	.503
242	yudixie_resnet50_object_class_0_240908	.503
243	mobilenet_v1_0.5_128	.503
244	deit_small_imagenet_full_seed-0	.502
245	BiT-M-R152x2	.502
246	resnext101_32x48d_wsl	.502
247	0.5x_resnet-18_LC_w_sh_100_iter	.502
248	BiT-S-R101x3	.502
249	RN50	.501
250	resnet_101_v2	.501
251	CORnet-Z	.501
252	cvt_cvt-21-384-in1k_4_LucyV4	.501
253	mobilenet_v2_0_5_224	.500
254	convnext_small_imagenet_100_seed-0	.500
255	mobilenet_v1_0.5_160	.500
256	resnext101_32x32d_wsl	.500
257	yudixie_resnet50_category_class_0_240908	.499
258	resnet_50_v2	.498
259	ViT_L_32_imagenet1k	.497
260	resnext101_32x16d_wsl	.497
261	alexnet	.496
262	alexnet	.496
263	alexnet	.496
264	alexnet	.496
265	alexnet	.496
266	alexnet	.496
267	alexnet-baseline	.496
268	alexnet	.496
269	alexnet	.496
270	alexnet_ks_torevert	.496
271	vision_transformer_vit_large_patch16_224	.495
272	BiT-M-R101x1	.495
273	imagenet_l2_3_0	.495
274	BiT-S-R152x2	.494
275	alexnet_random_linf8_perturb	.494
276	resnet50_byol	.494
277	ReAlnet10	.493
278	mobilenet_v2_0.35_128	.493
279	mobilenet_v1_0.25_224	.493
280	SWSL_resnext101_32x8d	.492
281	ReAlnet02	.492
282	ReAlnet01	.491
283	ReAlnet07	.491
284	ReAlnet06	.490
285	ReAlnet08	.490
286	ReAlnet04	.489
287	ReAlnet03	.489
288	mobilenet_v1_0.25_192	.489
289	ReAlnet09	.489
290	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.488
291	resnet50_linf_8_robust	.487
292	ReAlnet05	.486
293	BiT-S-R101x1	.486
294	mobilenet_v1_0.25_160	.486
295	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.486
296	alexnet_l2_3_robust	.486
297	alexnet	.485
298	VOneCORnet-S	.485
299	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.485
300	mobilenet_v2_0.5_96	.485
301	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.484
302	alexnet_reduced_aliasing_early_checkpoint	.483
303	fixres_resnext101_32x48d_wsl	.483
304	AlexNet_SIN	.479
305	cornet_s	.479
306	yudixie_resnet18_object_class_0_240719	.479
307	FrankRobWobv0	.478
308	yudixie_resnet18_category_class_0_240719	.477
309	vgg_19	.477
310	yudixie_resnet50_distance_translation_rotation_0_240908	.477
311	resnet_50_v1_spiking_l3	.476
312	resnet-18-LC_m	.476
313	yolos_tiny	.475
314	blt_vs	.475
315	yudixie_resnet50_translation_rotation_0_240908	.473
316	yudixie_resnet50_distance_translation_0_240908	.471
317	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.470
318	0.5x_resnet-18_LC	.470
319	resnet-18-LC_conv_init_m	.469
320	mobilenet_v2_0.35_96	.468
321	mobilenet_v1_0.25_128	.467
322	resnet18-colorization	.466
323	squeezenet1_0	.464
324	alexnet_robust_correct	.463
325	alexnet_early_checkpoint	.461
326	texture_shape_alexnet_trained_on_SIN	.461
327	vonealexnet_gaussian_noise_std4_fixed	.457
328	yudixie_resnet50_distance_reg_0_240908	.452
329	imagenet_l2_10_0	.449
330	resnet18-relative_position	.448
331	resnet-152_v2_pytorch	.448
332	yudixie_resnet50_rotation_reg_0_240908	.447
333	yudixie_resnet50_translation_reg_0_240908	.442
334	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.435
335	yudixie_resnet18_translation_rotation_0_240719	.434
336	resnet18-contrastive_predictive	.433
337	alexnet_linf_8_robust	.431
338	yudixie_resnet18_distance_translation_rotation_0_240719	.425
339	yudixie_resnet18_rotation_reg_0_240719	.422
340	yudixie_resnet18_distance_rotation_0_240719	.422
341	vggface	.419
342	yudixie_resnet50_distance_rotation_0_240908	.418
343	yudixie_resnet18_translation_reg_0_240719	.417
344	yudixie_resnet18_distance_translation_0_240719	.414
345	resnet18-depth_prediction	.408
346	deit_small_imagenet_100_seed-0	.402
347	yudixie_resnet18_distance_reg_0_240719	.402
348	r3m_resnet34	.400
349	briaai_rmbg_1_4	.398
350	r3m_resnet18	.393
351	r3m_resnet50	.391
352	artResNet18_1	.380
353	resnet50	.380
354	r3m_resnet50_nocrop	.375
355	resnet50-cifar	.359
356	resnet50_primary_visual_cortex	.355
357	prednet	.351
358	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.350
359	my-model	.346
360	resnet50_imagenet_10_seed-0	.329
361	CORnetZ_CIFAR10	.316
362	alexnet_training_seed_08	.296
363	v1-pyr-nodown	.295
364	alexnet_training_seed_03	.295
365	alexnet_training_seed_01	.293
366	alexnet_training_seed_02	.292
367	alexnet_training_seed_05	.291
368	alexnet_training_seed_04	.288
369	alexnet_training_seed_07	.288
370	alexnet_training_seed_09	.286
371	alexnet_training_seed_06	.282
372	alexnet_training_seed_10	.282
373	resnet50_FractalDB	.280
374	mobilevit_small	.276
375	CORnetZ_CIFAR10_bs32_20_04	.276
376	resnet18-autoencoder	.276
377	resnet50_imagenet_1_seed-0	.224
378	resnet-18_untrained	.223
379	yudixie_resnet18_random_0_240719	.221
380	resnet-50x2_untrained	.221
381	resnet50-meshes-lt-100-original-pretrained	.218
382	resnet50-meshes-lt-100-original-scratch	.217
383	resnet-50_untrained	.214
384	convnext_small_imagenet_10_seed-0	.208
385	yudixie_resnet50_random_0_240908	.201
386	resnet50_pretrained_with_retinal_waves	.183
387	resnet-18-LC_untrained	.179
388	fitvid_trained_on_physion	.166
389	deit_small_imagenet_10_seed-0	.118
390	deit_small_imagenet_1_seed-0	.095
391	convnext_small_imagenet_1_seed-0	.093
392	pixels	.072
393	my-model	.071
394	efficientnet-b4
395	efficientnet-b2
396	resnet_101_v1
397	resnet_152_v2
398	efficientnet-b6
399	vonegrcnn_52e_full
400	efficientnet-b0
401	xception
402	openclip
403	densenet_201_pytorch
404	hmax
405	resnet_152_v1
406	TAU
407	SimVP
408	PredRNN
409	pnasnet_large_pytorch
410	ConvLSTM
411	inception_v3_pytorch
412	resnet50_ImageNet
413	nasnet_large
414	densenet-201
415	pnasnet_large
416	inception_v4
417	AT_efficientnet-b0
418	MIM
419	vonegrcnn_62e_nobn
420	resnet18-simclr

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