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