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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("SanghaviMurty2020.IT-pls")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet-18-LC_w_sh_10_iter_m	.458
2	resnet50_robust_l2_eps1	.455
3	custom_model_cv_18_dagger_408	.453
4	resnet18-instance_recognition	.453
5	resnet-18-LC_w_sh_10_iter_conv_init_m	.449
6	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.449
7	resnet50-simclr-vissl	.440
8	resnet-18-LC_1st_conv_m	.437
9	ReAlnet08_cornet	.437
10	konkle_alexnetgn_ipcl_ref01_primary_model	.437
11	barlow-twins-resnet50	.436
12	voneresnet-50-robust	.436
13	resnet50-vicreg	.433
14	resnet50-barlow	.430
15	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.429
16	resnext101_32x8d_wsl	.428
17	ReAlnet07_cornet	.428
18	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.426
19	deit_base_imagenet_full_seed-0	.425
20	ReAlnet10_cornet	.425
21	convnext_small_imagenet_full_seed-0	.425
22	resnet-18-LC_w_sh_100_iter_m	.425
23	resnet50-vicregl0p9	.424
24	convnext_tiny_imagenet_full_seed-0	.424
25	resnet50_robust_l2_eps3	.423
26	resnet-18-LC_m	.421
27	resnet50-vicregl0p75	.421
28	vonegrcnn_62e_nobn	.420
29	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.420
30	vision_transformer_vit_large_patch16_224	.419
31	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.419
32	ReAlnet01_cornet	.419
33	voneresnet-50	.418
34	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.418
35	convnext_xlarge:fb_in22k_ft_in1k	.417
36	ReAlnet03_cornet	.417
37	convnext_large_imagenet_full_seed-0	.416
38	resnet50-moclr8deg	.416
39	vonegrcnn_52e_full	.416
40	vit_relpos_base_patch16_clsgap_224:sw_in1k	.416
41	ReAlnet02_cornet	.415
42	resnet-18-LC_w_sh_100_iter_conv_init_m	.415
43	inception_v1-tf	.413
44	resnet50-SIN_IN_IN	.411
45	resnet50_imagenet_100_seed-0	.411
46	nasnet_mobile	.410
47	convnext_base_imagenet_full_seed-0	.410
48	ReAlnet04_cornet	.410
49	ReAlnet05_cornet	.409
50	resnet18-local_aggregation	.409
51	densenet-201	.408
52	compact_resnet50_IT	.408
53	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.408
54	ReAlnet06_cornet	.408
55	ReAlnet09_cornet	.407
56	mobilenet_v2_1-4_224_pytorch	.407
57	resnet-50_v1-tf	.406
58	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.406
59	compact_cornets_IT	.405
60	cvt_cvt-13-384-in1k_4_LucyV4	.405
61	0.5x_resnet-18_LC_w_sh_1_iter	.402
62	mobilenet_v2_1.4_224-tf	.402
63	resnet-18-LC_w_sh_1_iter_m	.401
64	antialiased-r50	.401
65	grcnn	.400
66	ViT_L_32_imagenet1k	.400
67	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.400
68	efficientnet_b1_imagenet_full	.399
69	resnet101_ecoset_full	.399
70	densenet-201-keras	.398
71	0.5x_resnet-18_LC_w_sh_10_iter	.398
72	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.398
73	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.397
74	mobilenet_v2_1_4_224	.396
75	inception_v1	.395
76	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.395
77	resnet50_ecoset_full	.394
78	voneresnet-50-non_stochastic	.394
79	BiT-S-R152x4	.393
80	shufflenet_v2_x1_0	.392
81	resnet-18-LC_w_sh_1_iter_conv_init_m	.391
82	compact_resnet50_robust_IT	.391
83	cvt_cvt-21-224-in1k_4_LucyV4	.391
84	0.5x_resnet-18_LC	.391
85	mobilenet_v2_1.0_224-tf	.390
86	ReAlnet02_ALL	.390
87	resnet-101_v1-tf	.390
88	cvt_cvt-21-384-in1k_4_LucyV4	.389
89	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.389
90	CORnet-Z	.389
91	CORnet-S	.388
92	mobilenet_v2_1_0_224	.388
93	ReAlnet10_ALL	.387
94	ReAlnet01_ALL	.387
95	compact_vgg19_IT	.386
96	ReAlnet01_cornet_fov12	.386
97	cvt_cvt-13-224-in1k_4_LucyV4	.386
98	resnet50-SIN	.386
99	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.385
100	vit_large_patch14_clip_224:openai_ft_in1k	.384
101	ReAlnet03_ALL	.384
102	deit_large_imagenet_full_seed-0	.384
103	resnet50_imagenet_full	.384
104	cv_18_dagger_408_pretrained	.384
105	omnivore_swinB	.383
106	resnet-101_v2-tf	.383
107	ReAlnet06_ALL	.383
108	AT_efficientnet-b2	.383
109	ReAlnet05_ALL	.383
110	resnet-18-LC_d_w_sh_1x1_conv_init_m	.383
111	ReAlnet04_ALL	.382
112	resnet50_simclr	.382
113	grcnn_robust_v1	.382
114	resnet18-colorization	.381
115	omnivore_swinS	.381
116	ReAlnet09_ALL	.380
117	grcnn_v2_text_noise	.380
118	mobilenet_v2_0.75_160-tf	.379
119	resnet-50-pytorch	.379
120	resnet-50-robust	.379
121	convnext_tiny:in12k_ft_in1k	.379
122	resnet50-SIN_IN	.379
123	resnet-50_v2-tf	.378
124	resnet_50_v1_spiking	.378
125	resnet50-sup	.378
126	resnet_50_v1	.378
127	convnext_base:clip_laiona_augreg_ft_in1k_384	.378
128	antialiased-rnext101_32x8d	.378
129	vonegrcnn_47e	.377
130	ReAlnet08_ALL	.377
131	resnet50-VITO-8deg-cc	.377
132	mobilenet_v2_0_75_160	.376
133	Res2Net50_26w_4s	.376
134	resnet_SIN_IN_FT_IN	.376
135	vit_large_patch14_clip_224:laion2b_ft_in1k	.375
136	resnet50_l2_3_robust	.375
137	CLIP-RN50	.375
138	regnet_y_400mf	.375
139	omnivore_swinT	.374
140	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.374
141	alexnet_fov4	.373
142	resnet152_ecoset_full	.373
143	VOneCORnet-S	.373
144	mobilenet_v2_1_0_192	.373
145	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.372
146	grcnn_109	.372
147	nasnet_mobile-tf	.371
148	BiT-S-R50x3	.371
149	mobilenet_v2_1.3_224-tf	.371
150	nasnet_large-tf	.370
151	ReAlnet07_ALL	.370
152	resnet-152_v2-tf	.370
153	mobilenet_v2_1_0_128	.370
154	resnet18-contrastive_predictive	.370
155	densenet-121	.369
156	resnet50_linf_4_robust	.369
157	0.5x_resnet-18_LC_w_sh_100_iter	.368
158	resnet50_random_linf8_perturb	.368
159	resnet50-vitoimagevidnet8	.367
160	mobilenet_v1_0.75_160	.367
161	resnet-18-LC_conv_init_m	.366
162	densenet-121-keras	.366
163	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.366
164	mobilenet_v1_1.0_224	.365
165	mobilenet_v2_1_0_160	.365
166	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.364
167	deit_small_imagenet_full_seed-0	.364
168	AT_efficientnet-b4	.364
169	mobilenet_v2_0.75_192-tf	.363
170	BiT-M-R50x3	.363
171	mobilenet_v2_1_3_224	.363
172	CLIP_ViT-B_32	.362
173	yudixie_resnet50_imagenet1kpret_0_240908	.362
174	yudixie_resnet50_imagenet1kpret_0_240312	.362
175	resnet_50_v1_spiking_l4	.362
176	resnet_50_v1_spiking_l4a	.362
177	resnet50_tutorial	.362
178	mobilenet_v2_0.5_160	.362
179	FrankRobWobv0	.362
180	ViT-B/32	.361
181	texture_shape_resnet50_trained_on_SIN	.361
182	resnet152_imagenet_full	.361
183	AdvProp_efficientnet-b2	.360
184	resnet50	.360
185	0.5x_resnet-18	.360
186	imagenet_l2_3_0	.360
187	mobilenet_v2_1.0_128-tf	.360
188	vgg-19-keras	.360
189	inception_resnet_v2	.360
190	resnet50_imagenet_10_seed-0	.360
191	efficientnet_b2_imagenet_full	.359
192	alexnet_random_l2_3_perturb	.359
193	resnet50_random_l2_perturb	.358
194	resnet50_moco_v2	.358
195	resnet50_ewconplus_wzc	.357
196	effnetv2m_custom384	.357
197	alexnet_l2_3_robust	.357
198	mobilenet_v1_0.25_160	.356
199	resnet-18_test_m	.356
200	resnet-18	.356
201	AT_efficientnet-b7	.356
202	mobilenet_v1_0.75_192	.356
203	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.356
204	mobilenet_v2_0.75_128	.355
205	mobilenet_v1_1.0_160	.355
206	BiT-S-R152x2	.355
207	AdvProp_efficientnet-b4	.355
208	resnet34_ecoset_full	.354
209	vgg-16-keras	.354
210	efficientnet_b0	.354
211	mobilenet_v1_1.0_128	.354
212	resnet-152_v1-tf	.354
213	efficientnet_b0_imagenet_full	.354
214	yudixie_resnet18_imagenet1kpret_0_240719	.354
215	resnet18_ecoset_full	.353
216	mobilenet_v2_0.75_224-tf	.352
217	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.352
218	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.351
219	AdvProp_efficientnet-b7	.351
220	mobilenet_v2_0.35_96	.351
221	inception_v3-tf	.351
222	mobilenet_v1_0.75_224	.350
223	resnet50_linf_8_robust	.349
224	ReAlnet01_cornet_fov16	.349
225	mobilenet_v1_0.5_224	.349
226	mobilenet_v2_1.0_192-tf	.349
227	convnext_small_imagenet_100_seed-0	.348
228	convnext_large:fb_in22k_ft_in1k	.348
229	mobilenet_v2_0_75_224	.348
230	mobilenet_v1_1.0_192	.347
231	alexnet	.347
232	ReAlnet01_cornet_fov4	.347
233	RN50	.346
234	antialias-resnet152	.346
235	xception-keras	.346
236	vit_base_patch16_clip_224:openai_ft_in1k	.345
237	resnet_50_v2	.344
238	alexnet_random_linf8_perturb	.344
239	resnet34_imagenet_full	.344
240	alexnet_reduced_aliasing_early_checkpoint	.344
241	AdvProp_efficientnet-b6	.343
242	mobilenet_v1_0.5_160	.343
243	mobilenet_v2_0.5_128	.343
244	mobilenet_v2_0.5_192-tf	.342
245	resnet101	.341
246	resnet101_imagenet_full	.341
247	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.341
248	mobilenet_v2_0.35_160	.341
249	resnet_101_v2	.341
250	efficientnet-b7	.340
251	AdvProp_efficientnet-b0	.340
252	BiT-S-R50x1	.339
253	vonealexnet_gaussian_noise_std4_fixed	.339
254	mobilenet_v2_0_5_192	.339
255	vgg_16	.338
256	mobilenet_v2_1.0_160-tf	.338
257	densenet-169	.338
258	focalnet_tiny_lrf_in1k	.336
259	effnetb1_272x240	.336
260	squeezenet1_1	.335
261	resnet18_imagenet_full	.335
262	BiT-S-R101x3	.334
263	CLIP_resnet50	.334
264	CLIP_resnet50_float32	.334
265	inception_v3	.334
266	AlexNet_SIN	.332
267	inception_v2-tf	.332
268	r3m_resnet34	.331
269	densenet-169-keras	.331
270	mobilenet_v1_0.75_128	.331
271	resnet_50_v1_spiking_l3	.330
272	mobilenet_v2_0_75_192	.330
273	mobilenet_v2_0.35_128	.330
274	yolos_tiny	.329
275	resnext101_32x16d_wsl	.328
276	r3m_resnet18	.328
277	resnet50_byol	.328
278	mobilenet_v2_0.5_224-tf	.328
279	SWSL_resnet50	.328
280	mobilenet_v2_0.35_224	.327
281	resnet18-contrastive_multiview	.327
282	resnext101_32x48d_wsl	.326
283	pnasnet_large-tf	.325
284	resnet18-supervised	.322
285	convnext_femto_ols:d1_in1k	.322
286	mobilenet_v1_0.5_192	.322
287	mobilenet_v2_0.5_96	.321
288	mobilenet_v2_0.75_96	.321
289	fixres_resnext101_32x48d_wsl	.320
290	resnet18-deepcluster	.320
291	BiT-M-R50x1	.319
292	BiT-M-R152x4	.317
293	resnet18-relative_position	.316
294	convnext_tiny_sup	.315
295	BiT-S-R101x1	.315
296	AdvProp_efficientnet-b8	.315
297	resnext101_32x32d_wsl	.314
298	blt_vs	.314
299	mobilenet_v1_0.5_128	.314
300	resnet18_imagenet21kP	.314
301	alexnet_ks_torevert	.313
302	alexnet	.313
303	alexnet-baseline	.313
304	alexnet	.313
305	alexnet	.313
306	alexnet	.313
307	alexnet	.313
308	alexnet	.313
309	alexnet	.313
310	alexnet	.313
311	alexnet	.313
312	vit_large_patch14_clip_336:laion2b_ft_in1k	.312
313	yudixie_resnet50_object_class_0_240908	.312
314	imagenet_l2_10_0	.312
315	BiT-M-R101x3	.311
316	BiT-M-R152x2	.311
317	mobilenet_v1_0.25_192	.309
318	mobilenet_v2_0.35_192	.309
319	r3m_resnet50_nocrop	.308
320	r3m_resnet50	.308
321	RN50	.308
322	AlexNet_SIN_fov4	.307
323	mobilenet_v2_0_5_224	.306
324	texture_shape_alexnet_trained_on_SIN	.306
325	alexnet_linf_8_robust	.306
326	ReAlnet06	.305
327	resnet-34	.304
328	alexnet_fov12	.303
329	artResNet18_1	.302
330	deit_small_imagenet_100_seed-0	.302
331	ReAlnet09	.301
332	ReAlnet08	.301
333	alexnet_early_checkpoint	.300
334	mobilenet_v1_0.25_224	.298
335	ReAlnet01	.296
336	SWSL_resnext101_32x8d	.295
337	ReAlnet02	.295
338	briaai_rmbg_1_4	.294
339	ReAlnet05	.290
340	mobilenet_v2_1.0_96	.288
341	vgg_19	.288
342	ReAlnet07	.287
343	alexnet_robust_correct	.285
344	BiT-M-R101x1	.284
345	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.283
346	ReAlnet10	.282
347	ReAlnet04	.281
348	alexnet_fov16	.281
349	inception_v4-tf	.279
350	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.279
351	AlexNet_SIN_fov16	.275
352	ReAlnet03	.270
353	my-model	.268
354	yudixie_resnet50_distance_reg_0_240908	.267
355	squeezenet1_0	.265
356	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.262
357	AlexNet_SIN_fov12	.262
358	yudixie_resnet50_translation_rotation_0_240908	.261
359	cornet_s	.256
360	yudixie_resnet50_category_class_0_240908	.255
361	yudixie_resnet18_object_class_0_240719	.253
362	yudixie_resnet18_category_class_0_240719	.250
363	mobilenet_v1_0.25_128	.245
364	prednet	.241
365	yudixie_resnet50_distance_rotation_0_240908	.239
366	yudixie_resnet50_distance_translation_0_240908	.237
367	vggface	.235
368	yudixie_resnet50_distance_translation_rotation_0_240908	.234
369	resnet-152_v2_pytorch	.229
370	yudixie_resnet50_translation_reg_0_240908	.227
371	compact_resnet50_V4	.223
372	resnet18-depth_prediction	.223
373	resnet50_primary_visual_cortex	.220
374	resnet50	.219
375	yudixie_resnet50_rotation_reg_0_240908	.216
376	compact_resnet50_robust_V4	.215
377	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.213
378	CORnetZ_CIFAR10	.211
379	compact_vgg19_V4	.209
380	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.208
381	yudixie_resnet18_distance_translation_0_240719	.207
382	compact_cornets_V4	.200
383	yudixie_resnet18_distance_translation_rotation_0_240719	.190
384	alexnet_training_seed_08	.187
385	resnet50_imagenet_1_seed-0	.186
386	alexnet_training_seed_01_fov4	.186
387	alexnet_training_seed_02	.185
388	v1-pyr-nodown	.185
389	alexnet_training_seed_09	.180
390	alexnet_training_seed_07	.179
391	yudixie_resnet18_distance_rotation_0_240719	.178
392	resnet50-cifar	.176
393	alexnet_training_seed_10	.175
394	yudixie_resnet18_translation_rotation_0_240719	.173
395	alexnet_training_seed_01	.171
396	yudixie_resnet18_distance_reg_0_240719	.171
397	alexnet_training_seed_05	.169
398	yudixie_resnet18_rotation_reg_0_240719	.167
399	resnet50-meshes-lt-100-original-scratch	.160
400	alexnet_training_seed_01_fov12	.159
401	resnet-50_untrained	.158
402	mobilevit_small	.156
403	alexnet_training_seed_04	.153
404	resnet50_FractalDB	.152
405	alexnet_training_seed_06	.152
406	alexnet_training_seed_01_fov16	.151
407	yudixie_resnet18_translation_reg_0_240719	.150
408	resnet-18_untrained	.150
409	resnet-50x2_untrained	.148
410	yudixie_resnet18_random_0_240719	.144
411	resnet50_pretrained_with_retinal_waves	.140
412	resnet18-autoencoder	.134
413	yudixie_resnet50_random_0_240908	.133
414	convnext_small_imagenet_10_seed-0	.132
415	resnet50-meshes-lt-100-original-pretrained	.103
416	CORnetZ_CIFAR10_bs32_20_04	.095
417	fitvid_trained_on_physion	.076
418	resnet-18-LC_untrained	.072
419	convnext_small_imagenet_1_seed-0	.054
420	deit_small_imagenet_10_seed-0	.031
421	deit_small_imagenet_1_seed-0	.030
422	my-model	.015
423	pixels	.013
424	AT_efficientnet-b0
425	efficientnet-b0
426	efficientnet-b6
427	efficientnet-b2
428	efficientnet-b4
429	resnet18-simclr
430	openclip
431	resnet50_ImageNet
432	tv_efficientnet-b1
433	resnet_152_v1
434	ConvLSTM
435	PredRNN
436	SimVP
437	TAU
438	MIM
439	hmax
440	densenet_201_pytorch
441	pnasnet_large_pytorch
442	inception_v3_pytorch
443	inception_v4
444	xception
445	nasnet_large
446	pnasnet_large
447	vonegrcnn_62e_nobn
448	resnet_152_v2
449	vonegrcnn_47e
450	vonegrcnn_52e_full
451	resnet_101_v1
452	alexnet_training_seed_03

Benchmark bibtex

@misc{Sanghavi_Murty_DiCarlo_2021,
  title={SanghaviMurty2020},
  url={osf.io/fchme},
  DOI={10.17605/OSF.IO/FCHME},
  publisher={OSF},
  author={Sanghavi, Sachi and Murty, N A R and DiCarlo, James J},
  year={2021},
  month={Nov}
}

Ceiling

0.88.

Note that scores are relative to this ceiling.

Data: SanghaviMurty2020.IT

300 stimuli recordings from 29 sites in IT

Metric: pls