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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	.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	ReAlnet09_ALL	.541
70	convnext_tiny:in12k_ft_in1k	.540
71	ReAlnet06_ALL	.540
72	vonegrcnn_47e	.540
73	convnext_base_imagenet_full_seed-0	.540
74	mobilenet_v2_1.0_128-tf	.540
75	ReAlnet05_cornet	.540
76	resnet18-local_aggregation	.540
77	convnext_base:clip_laiona_augreg_ft_in1k_384	.540
78	voneresnet-50	.540
79	antialiased-r50	.540
80	densenet-169-keras	.540
81	efficientnet_b0	.539
82	resnet-101_v2-tf	.539
83	ReAlnet04_ALL	.539
84	ReAlnet03_ALL	.539
85	vonegrcnn_47e	.539
86	resnet50-SIN_IN_IN	.539
87	voneresnet-50-robust	.539
88	densenet-169	.539
89	mobilenet_v2_0.5_192-tf	.539
90	ReAlnet02_ALL	.539
91	ReAlnet10_ALL	.539
92	resnet-18-LC_w_sh_1_iter_m	.539
93	ReAlnet01_ALL	.538
94	0.5x_resnet-18_LC_w_sh_10_iter	.538
95	mobilenet_v2_0.75_128	.538
96	grcnn	.538
97	ReAlnet05_ALL	.538
98	mobilenet_v2_0.75_192-tf	.538
99	resnet_SIN_IN_FT_IN	.538
100	mobilenet_v2_0.35_192	.538
101	ReAlnet08_ALL	.537
102	nasnet_mobile-tf	.537
103	convnext_tiny_sup	.537
104	mobilenet_v2_1_0_160	.537
105	mobilenet_v2_1-4_224_pytorch	.537
106	resnet-18-LC_w_sh_100_iter_m	.537
107	resnet50_ecoset_full	.536
108	convnext_large_imagenet_full_seed-0	.536
109	resnet-50_v2-tf	.536
110	ReAlnet07_ALL	.536
111	resnet152_ecoset_full	.536
112	mobilenet_v2_1_0_192	.536
113	mobilenet_v2_1_4_224	.536
114	resnet_50_v1_spiking	.536
115	resnet_50_v1	.536
116	resnet50-sup	.536
117	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.535
118	mobilenet_v2_1_0_224	.535
119	voneresnet-50-non_stochastic	.535
120	mobilenet_v2_0.5_160	.535
121	CORnet-S	.534
122	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.534
123	mobilenet_v2_0.5_224-tf	.534
124	mobilenet_v2_1.0_224-tf	.534
125	mobilenet_v1_0.75_192	.534
126	mobilenet_v1_1.0_192	.533
127	resnet50_imagenet_100_seed-0	.533
128	resnet50_random_linf8_perturb	.533
129	shufflenet_v2_x1_0	.533
130	mobilenet_v1_1.0_160	.533
131	resnet-152_v2-tf	.532
132	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.532
133	resnet101_imagenet_full	.532
134	nasnet_large-tf	.532
135	mobilenet_v1_1.0_224	.531
136	grcnn_robust_v1	.531
137	mobilenet_v1_1.0_128	.531
138	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.530
139	densenet-121-keras	.530
140	convnext_large:fb_in22k_ft_in1k	.529
141	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.529
142	resnet34_ecoset_full	.529
143	mobilenet_v2_1_3_224	.529
144	densenet-121	.529
145	BiT-M-R50x3	.528
146	resnet152_imagenet_full	.528
147	resnet50-vitoimagevidnet8	.528
148	mobilenet_v1_0.75_160	.528
149	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.528
150	BiT-M-R50x1	.528
151	inception_v2-tf	.527
152	resnet_50_v1_spiking_l4	.527
153	resnet_50_v1_spiking_l4a	.527
154	resnet50_tutorial	.527
155	yudixie_resnet50_imagenet1kpret_0_240908	.527
156	yudixie_resnet50_imagenet1kpret_0_240312	.527
157	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.527
158	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.527
159	BiT-S-R50x3	.527
160	grcnn_109	.527
161	mobilenet_v2_0_75_192	.527
162	mobilenet_v2_1_0_128	.526
163	Res2Net50_26w_4s	.526
164	mobilenet_v2_0_5_192	.526
165	mobilenet_v2_0_75_160	.526
166	resnet18-supervised	.526
167	mobilenet_v2_0.35_160	.525
168	antialias-resnet152	.525
169	mobilenet_v2_0_75_224	.525
170	resnet50_linf_4_robust	.524
171	resnet50	.524
172	mobilenet_v2_0.5_128	.524
173	vit_large_patch14_clip_224:openai_ft_in1k	.524
174	resnet50_random_l2_perturb	.524
175	resnet50_moco_v2	.523
176	mobilenet_v2_0.35_224	.523
177	deit_large_imagenet_full_seed-0	.523
178	inception_v1-tf	.523
179	CLIP-RN50	.522
180	inception_v3-tf	.522
181	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.522
182	mobilenet_v1_0.75_224	.522
183	resnet50_l2_3_robust	.522
184	cv_18_dagger_408_pretrained	.522
185	deit_base_imagenet_full_seed-0	.522
186	focalnet_tiny_lrf_in1k	.521
187	yudixie_resnet18_imagenet1kpret_0_240719	.521
188	mobilenet_v1_0.75_128	.521
189	resnet101	.521
190	resnet34_imagenet_full	.521
191	BiT-S-R50x1	.521
192	grcnn_v2_text_noise	.520
193	regnet_y_400mf	.520
194	inception_v3	.520
195	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.520
196	resnet50_robust_l2_eps3	.520
197	BiT-S-R152x4	.519
198	convnext_femto_ols:d1_in1k	.519
199	inception_resnet_v2	.518
200	resnet18_ecoset_full	.518
201	vit_large_patch14_clip_224:laion2b_ft_in1k	.517
202	resnet18_imagenet_full	.517
203	cvt_cvt-13-224-in1k_4_LucyV4	.517
204	omnivore_swinS	.517
205	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.517
206	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.516
207	resnext101_32x8d_wsl	.516
208	RN50	.516
209	omnivore_swinB	.516
210	texture_shape_resnet50_trained_on_SIN	.515
211	0.5x_resnet-18	.514
212	resnet-18_test_m	.514
213	resnet-18	.514
214	vgg-16-keras	.514
215	inception_v1	.513
216	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.513
217	resnet18_imagenet21kP	.513
218	BiT-M-R101x3	.513
219	BiT-M-R152x4	.512
220	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.512
221	cvt_cvt-21-224-in1k_4_LucyV4	.512
222	resnet18-contrastive_multiview	.511
223	vgg_16	.511
224	ViT-B/32	.511
225	omnivore_swinT	.510
226	resnet-18-LC_1st_conv_m	.510
227	inception_v4-tf	.510
228	SWSL_resnet50	.509
229	vit_large_patch14_clip_336:laion2b_ft_in1k	.509
230	resnet50-VITO-8deg-cc	.509
231	cvt_cvt-13-384-in1k_4_LucyV4	.509
232	resnet18-deepcluster	.509
233	CLIP_ViT-B_32	.508
234	resnet50_simclr	.508
235	mobilenet_v1_0.5_192	.508
236	mobilenet_v2_1.0_96	.508
237	xception-keras	.508
238	resnet-18-LC_d_w_sh_1x1_conv_init_m	.508
239	CLIP_resnet50_float32	.507
240	CLIP_resnet50	.507
241	resnet-50-pytorch	.507
242	resnet-50-robust	.507
243	vit_base_patch16_clip_224:openai_ft_in1k	.507
244	alexnet_random_l2_3_perturb	.506
245	mobilenet_v1_0.5_224	.506
246	resnet-34	.505
247	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.505
248	squeezenet1_1	.504
249	vgg-19-keras	.504
250	mobilenet_v2_0.75_96	.503
251	pnasnet_large-tf	.503
252	yudixie_resnet50_object_class_0_240908	.503
253	mobilenet_v1_0.5_128	.503
254	deit_small_imagenet_full_seed-0	.502
255	BiT-M-R152x2	.502
256	resnext101_32x48d_wsl	.502
257	0.5x_resnet-18_LC_w_sh_100_iter	.502
258	BiT-S-R101x3	.502
259	RN50	.501
260	resnet_101_v2	.501
261	CORnet-Z	.501
262	cvt_cvt-21-384-in1k_4_LucyV4	.501
263	mobilenet_v2_0_5_224	.500
264	convnext_small_imagenet_100_seed-0	.500
265	mobilenet_v1_0.5_160	.500
266	resnext101_32x32d_wsl	.500
267	yudixie_resnet50_category_class_0_240908	.499
268	resnet_50_v2	.498
269	ViT_L_32_imagenet1k	.497
270	resnext101_32x16d_wsl	.497
271	alexnet	.496
272	alexnet	.496
273	alexnet	.496
274	alexnet	.496
275	alexnet	.496
276	alexnet	.496
277	alexnet-baseline	.496
278	alexnet	.496
279	alexnet	.496
280	alexnet_ks_torevert	.496
281	vision_transformer_vit_large_patch16_224	.495
282	BiT-M-R101x1	.495
283	imagenet_l2_3_0	.495
284	BiT-S-R152x2	.494
285	alexnet_random_linf8_perturb	.494
286	resnet50_byol	.494
287	ReAlnet10	.493
288	mobilenet_v2_0.35_128	.493
289	mobilenet_v1_0.25_224	.493
290	SWSL_resnext101_32x8d	.492
291	ReAlnet02	.492
292	ReAlnet01	.491
293	ReAlnet07	.491
294	ReAlnet06	.490
295	ReAlnet08	.490
296	ReAlnet04	.489
297	ReAlnet03	.489
298	mobilenet_v1_0.25_192	.489
299	ReAlnet09	.489
300	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.488
301	resnet50_linf_8_robust	.487
302	ReAlnet05	.486
303	BiT-S-R101x1	.486
304	mobilenet_v1_0.25_160	.486
305	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.486
306	alexnet_l2_3_robust	.486
307	alexnet	.485
308	VOneCORnet-S	.485
309	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.485
310	mobilenet_v2_0.5_96	.485
311	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.484
312	alexnet_reduced_aliasing_early_checkpoint	.483
313	fixres_resnext101_32x48d_wsl	.483
314	AlexNet_SIN	.479
315	cornet_s	.479
316	yudixie_resnet18_object_class_0_240719	.479
317	FrankRobWobv0	.478
318	yudixie_resnet18_category_class_0_240719	.477
319	vgg_19	.477
320	yudixie_resnet50_distance_translation_rotation_0_240908	.477
321	resnet_50_v1_spiking_l3	.476
322	resnet-18-LC_m	.476
323	yolos_tiny	.475
324	blt_vs	.475
325	yudixie_resnet50_translation_rotation_0_240908	.473
326	yudixie_resnet50_distance_translation_0_240908	.471
327	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.470
328	0.5x_resnet-18_LC	.470
329	resnet-18-LC_conv_init_m	.469
330	mobilenet_v2_0.35_96	.468
331	mobilenet_v1_0.25_128	.467
332	resnet18-colorization	.466
333	squeezenet1_0	.464
334	alexnet_robust_correct	.463
335	alexnet_early_checkpoint	.461
336	texture_shape_alexnet_trained_on_SIN	.461
337	vonealexnet_gaussian_noise_std4_fixed	.457
338	yudixie_resnet50_distance_reg_0_240908	.452
339	imagenet_l2_10_0	.449
340	resnet18-relative_position	.448
341	resnet-152_v2_pytorch	.448
342	yudixie_resnet50_rotation_reg_0_240908	.447
343	yudixie_resnet50_translation_reg_0_240908	.442
344	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.435
345	yudixie_resnet18_translation_rotation_0_240719	.434
346	resnet18-contrastive_predictive	.433
347	alexnet_linf_8_robust	.431
348	yudixie_resnet18_distance_translation_rotation_0_240719	.425
349	yudixie_resnet18_rotation_reg_0_240719	.422
350	yudixie_resnet18_distance_rotation_0_240719	.422
351	vggface	.419
352	yudixie_resnet50_distance_rotation_0_240908	.418
353	yudixie_resnet18_translation_reg_0_240719	.417
354	yudixie_resnet18_distance_translation_0_240719	.414
355	resnet18-depth_prediction	.408
356	deit_small_imagenet_100_seed-0	.402
357	yudixie_resnet18_distance_reg_0_240719	.402
358	r3m_resnet34	.400
359	briaai_rmbg_1_4	.398
360	r3m_resnet18	.393
361	r3m_resnet50	.391
362	artResNet18_1	.380
363	resnet50	.380
364	r3m_resnet50_nocrop	.375
365	resnet50-cifar	.359
366	resnet50_primary_visual_cortex	.355
367	prednet	.351
368	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.350
369	my-model	.346
370	resnet50_imagenet_10_seed-0	.329
371	CORnetZ_CIFAR10	.316
372	alexnet_training_seed_08	.296
373	v1-pyr-nodown	.295
374	alexnet_training_seed_03	.295
375	alexnet_training_seed_01	.293
376	alexnet_training_seed_02	.292
377	alexnet_training_seed_05	.291
378	alexnet_training_seed_04	.288
379	alexnet_training_seed_07	.288
380	alexnet_training_seed_09	.286
381	alexnet_training_seed_06	.282
382	alexnet_training_seed_10	.282
383	resnet50_FractalDB	.280
384	mobilevit_small	.276
385	CORnetZ_CIFAR10_bs32_20_04	.276
386	resnet18-autoencoder	.276
387	resnet50_imagenet_1_seed-0	.224
388	resnet-18_untrained	.223
389	yudixie_resnet18_random_0_240719	.221
390	resnet-50x2_untrained	.221
391	resnet50-meshes-lt-100-original-pretrained	.218
392	resnet50-meshes-lt-100-original-scratch	.217
393	resnet-50_untrained	.214
394	convnext_small_imagenet_10_seed-0	.208
395	yudixie_resnet50_random_0_240908	.201
396	resnet50_pretrained_with_retinal_waves	.183
397	resnet-18-LC_untrained	.179
398	fitvid_trained_on_physion	.166
399	deit_small_imagenet_10_seed-0	.118
400	deit_small_imagenet_1_seed-0	.095
401	convnext_small_imagenet_1_seed-0	.093
402	pixels	.072
403	my-model	.071
404	AT_efficientnet-b0
405	efficientnet-b0
406	efficientnet-b6
407	efficientnet-b2
408	efficientnet-b4
409	resnet18-simclr
410	openclip
411	resnet50_ImageNet
412	resnet_152_v1
413	densenet-201
414	ConvLSTM
415	PredRNN
416	SimVP
417	TAU
418	MIM
419	hmax
420	densenet_201_pytorch
421	pnasnet_large_pytorch
422	inception_v3_pytorch
423	inception_v4
424	xception
425	nasnet_large
426	pnasnet_large
427	vonegrcnn_62e_nobn
428	resnet_101_v1
429	resnet_152_v2
430	vonegrcnn_52e_full

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