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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("SanghaviJozwik2020.IT-pls")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet50_robust_l2_eps3	.585
2	AT_efficientnet-b7	.569
3	resnet50-vicregl0p9	.566
4	resnet-18-LC_w_sh_100_iter_conv_init_m	.565
5	resnet50_robust_l2_eps1	.565
6	resnet-18-LC_w_sh_10_iter_m	.563
7	voneresnet-50-robust	.563
8	barlow-twins-resnet50	.562
9	resnet-18-LC_w_sh_100_iter_m	.562
10	resnet50-barlow	.560
11	resnet-50-robust	.560
12	resnet-50-pytorch	.560
13	resnet50-vicreg	.560
14	resnet-18-LC_w_sh_1_iter_conv_init_m	.557
15	AdvProp_efficientnet-b6	.554
16	custom_model_cv_18_dagger_408	.553
17	AdvProp_efficientnet-b7	.552
18	resnet-18-LC_d_w_sh_1x1_conv_init_m	.552
19	resnet-18-LC_w_sh_10_iter_conv_init_m	.552
20	alexnet_robust_correct	.550
21	convnext_tiny_imagenet_full_seed-0	.550
22	resnet50-vicregl0p75	.548
23	convnext_small_imagenet_full_seed-0	.548
24	AdvProp_efficientnet-b8	.548
25	resnet50-simclr-vissl	.546
26	0.5x_resnet-18_LC_w_sh_1_iter	.546
27	AT_efficientnet-b4	.543
28	0.5x_resnet-18_LC_w_sh_10_iter	.541
29	AT_efficientnet-b2	.541
30	AdvProp_efficientnet-b4	.538
31	vonegrcnn_62e_nobn	.538
32	vonegrcnn_52e_full	.538
33	convnext_base_imagenet_full_seed-0	.538
34	mobilenet_v2_0.5_160	.537
35	voneresnet-50	.536
36	resnet50_random_linf8_perturb	.536
37	mobilenet_v2_0.75_128	.535
38	convnext_large_imagenet_full_seed-0	.535
39	mobilenet_v2_1.0_96	.535
40	konkle_alexnetgn_ipcl_ref01_primary_model	.534
41	alexnet_l2_3_robust	.534
42	mobilenet_v2_0.75_96	.534
43	resnet50_random_l2_perturb	.533
44	resnet50_l2_3_robust	.532
45	AdvProp_efficientnet-b2	.532
46	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.532
47	mobilenet_v2_0.5_96	.531
48	resnet-50_v1-tf	.530
49	vit_relpos_base_patch16_clsgap_224:sw_in1k	.530
50	resnet-152_v1-tf	.529
51	tv_efficientnet-b1	.529
52	imagenet_l2_10_0	.529
53	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.529
54	resnet18-instance_recognition	.529
55	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.527
56	convnext_xlarge:fb_in22k_ft_in1k	.527
57	mobilenet_v1_1.0_128	.527
58	resnet50-VITO-8deg-cc	.527
59	resnet-18-LC_w_sh_1_iter_m	.527
60	mobilenet_v2_1.0_128-tf	.527
61	vision_transformer_vit_large_patch16_224	.525
62	mobilenet_v2_0.5_128	.525
63	AdvProp_efficientnet-b0	.525
64	resnet50-vitoimagevidnet8	.524
65	resnet50_imagenet_full	.524
66	Res2Net50_26w_4s	.523
67	vonegrcnn_47e	.523
68	effnetv2m_custom384	.523
69	mobilenet_v2_0.35_160	.523
70	resnet50_ecoset_full	.523
71	mobilenet_v2_1_0_128	.522
72	resnet50-moclr8deg	.521
73	resnet50_linf_8_robust	.521
74	imagenet_l2_3_0	.521
75	resnet-101_v1-tf	.520
76	0.5x_resnet-18_LC_w_sh_100_iter	.520
77	ReAlnet08_cornet	.520
78	cvt_cvt-13-224-in1k_4_LucyV4	.519
79	deit_base_imagenet_full_seed-0	.519
80	mobilenet_v2_0.35_96	.519
81	mobilenet_v2_0.75_160-tf	.519
82	resnet50_ewconplus_wzc	.519
83	cv_18_dagger_408_pretrained	.518
84	ReAlnet10_cornet	.518
85	vonegrcnn_47e	.518
86	ReAlnet03_cornet	.518
87	resnet101	.517
88	resnet50	.517
89	voneresnet-50-non_stochastic	.517
90	mobilenet_v2_0_75_160	.516
91	ReAlnet06_cornet	.515
92	ReAlnet07_cornet	.515
93	resnet50_imagenet_100_seed-0	.515
94	nasnet_mobile	.515
95	ReAlnet02_cornet	.515
96	mobilenet_v2_0.5_192-tf	.515
97	resnet50_linf_4_robust	.514
98	yudixie_resnet50_imagenet1kpret_0_240312	.514
99	resnet_50_v1_spiking_l4	.514
100	resnet_50_v1_spiking_l4a	.514
101	resnet50_tutorial	.514
102	yudixie_resnet50_imagenet1kpret_0_240908	.514
103	resnet50-SIN_IN_IN	.514
104	efficientnet_b0_imagenet_full	.513
105	ReAlnet04_cornet	.513
106	mobilenet_v2_0.75_192-tf	.513
107	ReAlnet09_cornet	.513
108	efficientnet_b1_imagenet_full	.513
109	omnivore_swinT	.512
110	ViT_L_32_imagenet1k	.512
111	mobilenet_v1_1.0_160	.512
112	ReAlnet01_cornet	.512
113	mobilenet_v2_1_4_224	.512
114	resnet-18-LC_1st_conv_m	.511
115	mobilenet_v2_1-4_224_pytorch	.511
116	ReAlnet05_cornet	.510
117	resnet-18-LC_m	.510
118	efficientnet-b7	.509
119	mobilenet_v2_0.35_128	.508
120	resnet152_imagenet_full	.507
121	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.507
122	resnet50-SIN_IN	.507
123	mobilenet_v2_1.0_160-tf	.506
124	mobilenet_v2_1.3_224-tf	.506
125	antialias-resnet152	.506
126	convnext_tiny:in12k_ft_in1k	.506
127	regnet_y_400mf	.505
128	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.505
129	resnext101_32x8d_wsl	.504
130	mobilenet_v2_0.35_192	.504
131	mobilenet_v2_0.5_224-tf	.504
132	resnet101_ecoset_full	.504
133	cvt_cvt-21-224-in1k_4_LucyV4	.504
134	resnet-50_v2-tf	.503
135	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.503
136	omnivore_swinB	.503
137	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.503
138	resnet-101_v2-tf	.503
139	mobilenet_v2_1_0_160	.503
140	BiT-S-R152x4	.503
141	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.503
142	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.502
143	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.502
144	mobilenet_v2_0.75_224-tf	.502
145	mobilenet_v1_0.75_160	.501
146	mobilenet_v2_0_5_192	.501
147	mobilenet_v2_1.4_224-tf	.501
148	efficientnet_b2_imagenet_full	.501
149	CORnet-S	.501
150	ViT-B/32	.500
151	effnetb1_272x240	.500
152	mobilenet_v2_1.0_192-tf	.500
153	grcnn	.500
154	efficientnet_b0	.500
155	mobilenet_v2_0_75_192	.499
156	focalnet_tiny_lrf_in1k	.499
157	cvt_cvt-13-384-in1k_4_LucyV4	.499
158	alexnet_linf_8_robust	.499
159	CLIP_ViT-B_32	.498
160	inception_v1-tf	.498
161	ReAlnet03_ALL	.498
162	ReAlnet07_ALL	.498
163	ReAlnet10_ALL	.498
164	ReAlnet01_ALL	.498
165	BiT-M-R152x4	.497
166	resnet152_ecoset_full	.497
167	ReAlnet02_ALL	.497
168	ReAlnet08_ALL	.497
169	cvt_cvt-21-384-in1k_4_LucyV4	.496
170	omnivore_swinS	.496
171	resnet34_ecoset_full	.496
172	FrankRobWobv0	.496
173	mobilenet_v1_0.5_192	.496
174	ReAlnet04_ALL	.496
175	0.5x_resnet-18_LC	.495
176	antialiased-r50	.495
177	ReAlnet06_ALL	.495
178	mobilenet_v2_0.35_224	.495
179	convnext_base:clip_laiona_augreg_ft_in1k_384	.495
180	ReAlnet09_ALL	.495
181	ReAlnet05_ALL	.495
182	antialiased-rnext101_32x8d	.494
183	densenet-201-keras	.494
184	densenet-201	.493
185	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.493
186	mobilenet_v2_1_0_224	.493
187	mobilenet_v1_0.25_160	.493
188	0.5x_resnet-18	.492
189	resnet-18-LC_conv_init_m	.492
190	mobilenet_v2_1.0_224-tf	.492
191	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.491
192	mobilenet_v2_1_0_192	.491
193	shufflenet_v2_x1_0	.491
194	deit_large_imagenet_full_seed-0	.491
195	convnext_large:fb_in22k_ft_in1k	.490
196	densenet-169	.489
197	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.489
198	mobilenet_v2_0_75_224	.487
199	resnet101_imagenet_full	.487
200	grcnn_robust_v1	.487
201	mobilenet_v1_0.75_192	.487
202	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.487
203	grcnn_109	.486
204	mobilenet_v1_1.0_192	.486
205	nasnet_mobile-tf	.484
206	deit_small_imagenet_full_seed-0	.484
207	resnet50-SIN	.484
208	nasnet_large-tf	.483
209	yudixie_resnet18_imagenet1kpret_0_240719	.483
210	mobilenet_v1_0.5_128	.483
211	densenet-169-keras	.482
212	mobilenet_v1_0.25_192	.482
213	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.482
214	SWSL_resnet50	.481
215	mobilenet_v1_0.75_224	.481
216	resnet_50_v1_spiking	.480
217	resnet50-sup	.480
218	resnet_50_v1	.480
219	convnext_small_imagenet_100_seed-0	.479
220	inception_v1	.478
221	resnet-152_v2-tf	.478
222	mobilenet_v2_1_3_224	.477
223	alexnet_random_l2_3_perturb	.476
224	mobilenet_v1_1.0_224	.476
225	texture_shape_resnet50_trained_on_SIN	.475
226	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.473
227	resnet18_imagenet_full	.473
228	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.473
229	mobilenet_v1_0.75_128	.473
230	mobilenet_v1_0.5_160	.473
231	densenet-121	.472
232	resnet_SIN_IN_FT_IN	.472
233	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.472
234	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.472
235	resnet18_ecoset_full	.471
236	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.471
237	CLIP_resnet50_float32	.471
238	CLIP_resnet50	.471
239	alexnet_ks_torevert	.471
240	alexnet	.471
241	alexnet	.471
242	alexnet	.471
243	alexnet	.471
244	alexnet	.471
245	alexnet	.471
246	alexnet-baseline	.471
247	alexnet	.471
248	alexnet	.471
249	grcnn_v2_text_noise	.471
250	vit_large_patch14_clip_224:laion2b_ft_in1k	.468
251	resnet50_simclr	.468
252	resnet18-deepcluster	.468
253	densenet-121-keras	.468
254	resnet18-local_aggregation	.467
255	resnet18_imagenet21kP	.467
256	RN50	.466
257	mobilenet_v1_0.5_224	.466
258	resnet_50_v1_spiking_l3	.466
259	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.466
260	alexnet_random_linf8_perturb	.465
261	BiT-S-R152x2	.465
262	mobilenet_v2_0_5_224	.465
263	vit_large_patch14_clip_224:openai_ft_in1k	.464
264	mobilenet_v1_0.25_128	.463
265	CORnet-Z	.462
266	deit_small_imagenet_100_seed-0	.459
267	CLIP-RN50	.459
268	convnext_femto_ols:d1_in1k	.458
269	mobilenet_v1_0.25_224	.457
270	resnet18-supervised	.457
271	BiT-S-R50x3	.457
272	BiT-M-R50x3	.456
273	squeezenet1_1	.456
274	vonealexnet_gaussian_noise_std4_fixed	.456
275	inception_resnet_v2	.453
276	resnet50_moco_v2	.453
277	vgg-16-keras	.452
278	resnet_50_v2	.450
279	alexnet	.450
280	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.448
281	vgg_16	.447
282	resnet34_imagenet_full	.446
283	xception-keras	.446
284	resnext101_32x48d_wsl	.446
285	resnet50_byol	.445
286	convnext_tiny_sup	.443
287	RN50	.442
288	inception_v2-tf	.442
289	vgg_19	.441
290	alexnet_reduced_aliasing_early_checkpoint	.440
291	BiT-M-R50x1	.440
292	vit_base_patch16_clip_224:openai_ft_in1k	.439
293	resnext101_32x16d_wsl	.439
294	r3m_resnet18	.439
295	resnet-18_test_m	.439
296	resnet-18	.439
297	inception_v3	.437
298	resnet50_primary_visual_cortex	.437
299	VOneCORnet-S	.436
300	vgg-19-keras	.433
301	briaai_rmbg_1_4	.431
302	artResNet18_1	.431
303	resnet-34	.428
304	resnext101_32x32d_wsl	.428
305	alexnet_early_checkpoint	.427
306	blt_vs	.427
307	BiT-S-R50x1	.425
308	AlexNet_SIN	.424
309	inception_v3-tf	.423
310	r3m_resnet34	.423
311	vit_large_patch14_clip_336:laion2b_ft_in1k	.423
312	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.423
313	yudixie_resnet50_object_class_0_240908	.420
314	resnet18-colorization	.419
315	SWSL_resnext101_32x8d	.418
316	resnet18-contrastive_multiview	.414
317	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.411
318	texture_shape_alexnet_trained_on_SIN	.410
319	pnasnet_large-tf	.410
320	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.403
321	yolos_tiny	.402
322	resnet18-relative_position	.398
323	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.397
324	yudixie_resnet50_category_class_0_240908	.396
325	BiT-M-R101x1	.391
326	BiT-M-R101x3	.388
327	BiT-S-R101x1	.386
328	BiT-S-R101x3	.384
329	inception_v4-tf	.381
330	BiT-M-R152x2	.380
331	ReAlnet06	.378
332	ReAlnet05	.376
333	ReAlnet07	.376
334	ReAlnet04	.374
335	ReAlnet10	.373
336	ReAlnet01	.373
337	ReAlnet03	.372
338	ReAlnet08	.372
339	squeezenet1_0	.371
340	ReAlnet09	.371
341	resnet18-contrastive_predictive	.370
342	resnet50_imagenet_10_seed-0	.370
343	ReAlnet02	.369
344	r3m_resnet50	.366
345	yudixie_resnet50_distance_reg_0_240908	.364
346	vggface	.364
347	yudixie_resnet50_translation_rotation_0_240908	.363
348	yudixie_resnet18_category_class_0_240719	.362
349	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.362
350	cornet_s	.361
351	resnet50-cifar	.360
352	yudixie_resnet50_distance_translation_rotation_0_240908	.357
353	yudixie_resnet18_object_class_0_240719	.356
354	yudixie_resnet50_distance_rotation_0_240908	.356
355	resnet-152_v2_pytorch	.355
356	yudixie_resnet50_distance_translation_0_240908	.344
357	yudixie_resnet50_translation_reg_0_240908	.343
358	yudixie_resnet50_rotation_reg_0_240908	.343
359	resnet18-depth_prediction	.338
360	CORnetZ_CIFAR10	.333
361	resnet50	.330
362	alexnet_training_seed_02	.322
363	alexnet_training_seed_06	.320
364	alexnet_training_seed_03	.317
365	alexnet_training_seed_08	.315
366	alexnet_training_seed_05	.311
367	alexnet_training_seed_01	.309
368	alexnet_training_seed_10	.306
369	alexnet_training_seed_09	.304
370	alexnet_training_seed_04	.302
371	resnet50_FractalDB	.301
372	compact_resnet50_robust_IT	.300
373	compact_resnet50_IT	.298
374	prednet	.297
375	mobilevit_small	.295
376	alexnet_training_seed_07	.295
377	yudixie_resnet18_translation_rotation_0_240719	.294
378	compact_cornets_IT	.288
379	my-model	.283
380	yudixie_resnet18_distance_rotation_0_240719	.277
381	yudixie_resnet18_distance_translation_0_240719	.272
382	compact_vgg19_IT	.271
383	yudixie_resnet18_translation_reg_0_240719	.268
384	yudixie_resnet18_distance_translation_rotation_0_240719	.267
385	resnet-50x2_untrained	.265
386	yudixie_resnet18_rotation_reg_0_240719	.259
387	convnext_small_imagenet_10_seed-0	.256
388	yudixie_resnet18_distance_reg_0_240719	.255
389	CORnetZ_CIFAR10_bs32_20_04	.250
390	resnet50_imagenet_1_seed-0	.250
391	yudixie_resnet50_random_0_240908	.243
392	yudixie_resnet18_random_0_240719	.237
393	resnet50-meshes-lt-100-original-scratch	.237
394	resnet-18_untrained	.223
395	resnet18-autoencoder	.220
396	resnet50_pretrained_with_retinal_waves	.207
397	resnet-50_untrained	.204
398	resnet-18-LC_untrained	.192
399	compact_cornets_V4	.192
400	v1-pyr-nodown	.190
401	resnet50-meshes-lt-100-original-pretrained	.175
402	compact_vgg19_V4	.145
403	compact_resnet50_robust_V4	.129
404	compact_resnet50_V4	.118
405	deit_small_imagenet_1_seed-0	.056
406	deit_small_imagenet_10_seed-0	.053
407	convnext_small_imagenet_1_seed-0	.041
408	pixels	.038
409	my-model	.022
410	AT_efficientnet-b0
411	fixres_resnext101_32x48d_wsl
412	efficientnet-b0
413	efficientnet-b6
414	efficientnet-b2
415	efficientnet-b4
416	resnet18-simclr
417	r3m_resnet50_nocrop
418	fitvid_trained_on_physion
419	openclip
420	resnet50_ImageNet
421	resnet_152_v1
422	resnet_101_v2
423	ConvLSTM
424	PredRNN
425	SimVP
426	TAU
427	MIM
428	hmax
429	densenet_201_pytorch
430	pnasnet_large_pytorch
431	inception_v3_pytorch
432	inception_v4
433	xception
434	nasnet_large
435	pnasnet_large
436	vonegrcnn_62e_nobn
437	resnet_152_v2
438	resnet_101_v1
439	vonegrcnn_52e_full

Benchmark bibtex

@misc{Sanghavi_Jozwik_DiCarlo_2021,
  title={SanghaviJozwik2020},
  url={osf.io/fhy36},
  DOI={10.17605/OSF.IO/FHY36},
  publisher={OSF},
  author={Sanghavi, Sachi and Jozwik, Kamila M and DiCarlo, James J},
  year={2021},
  month={Nov}
}

Ceiling

0.86.

Note that scores are relative to this ceiling.

Data: SanghaviJozwik2020.IT

4916 stimuli recordings from 26 sites in IT

Metric: pls