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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	.401
2	resnet50_robust_l2_eps1	.398
3	custom_model_cv_18_dagger_408	.397
4	resnet18-instance_recognition	.397
5	resnet-18-LC_w_sh_10_iter_conv_init_m	.393
6	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.393
7	resnet50-simclr-vissl	.385
8	resnet-18-LC_1st_conv_m	.383
9	ReAlnet08_cornet	.383
10	konkle_alexnetgn_ipcl_ref01_primary_model	.383
11	barlow-twins-resnet50	.382
12	voneresnet-50-robust	.381
13	resnet50-vicreg	.379
14	resnet50-barlow	.377
15	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.376
16	resnext101_32x8d_wsl	.375
17	ReAlnet07_cornet	.374
18	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.373
19	deit_base_imagenet_full_seed-0	.372
20	ReAlnet10_cornet	.372
21	convnext_small_imagenet_full_seed-0	.372
22	resnet-18-LC_w_sh_100_iter_m	.372
23	resnet50-vicregl0p9	.371
24	convnext_tiny_imagenet_full_seed-0	.371
25	resnet50_robust_l2_eps3	.370
26	resnet-18-LC_m	.369
27	resnet50-vicregl0p75	.368
28	vonegrcnn_62e_nobn	.367
29	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.367
30	vision_transformer_vit_large_patch16_224	.367
31	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.367
32	ReAlnet01_cornet	.367
33	voneresnet-50	.366
34	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.366
35	convnext_xlarge:fb_in22k_ft_in1k	.365
36	ReAlnet03_cornet	.365
37	convnext_large_imagenet_full_seed-0	.365
38	resnet50-moclr8deg	.365
39	vonegrcnn_52e_full	.364
40	vit_relpos_base_patch16_clsgap_224:sw_in1k	.364
41	ReAlnet02_cornet	.364
42	resnet-18-LC_w_sh_100_iter_conv_init_m	.363
43	inception_v1-tf	.362
44	resnet50-SIN_IN_IN	.360
45	resnet50_imagenet_100_seed-0	.360
46	nasnet_mobile	.359
47	convnext_base_imagenet_full_seed-0	.359
48	ReAlnet04_cornet	.359
49	ReAlnet05_cornet	.358
50	resnet18-local_aggregation	.358
51	densenet-201	.358
52	compact_resnet50_IT	.357
53	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.357
54	ReAlnet06_cornet	.357
55	ReAlnet09_cornet	.356
56	mobilenet_v2_1-4_224_pytorch	.356
57	resnet-50_v1-tf	.356
58	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.356
59	compact_cornets_IT	.355
60	cvt_cvt-13-384-in1k_4_LucyV4	.354
61	0.5x_resnet-18_LC_w_sh_1_iter	.352
62	mobilenet_v2_1.4_224-tf	.352
63	resnet-18-LC_w_sh_1_iter_m	.351
64	antialiased-r50	.351
65	grcnn	.351
66	ViT_L_32_imagenet1k	.351
67	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.350
68	efficientnet_b1_imagenet_full	.350
69	resnet101_ecoset_full	.350
70	densenet-201-keras	.349
71	0.5x_resnet-18_LC_w_sh_10_iter	.349
72	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.348
73	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.347
74	mobilenet_v2_1_4_224	.347
75	inception_v1	.346
76	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.346
77	resnet50_ecoset_full	.345
78	voneresnet-50-non_stochastic	.345
79	BiT-S-R152x4	.344
80	shufflenet_v2_x1_0	.343
81	resnet-18-LC_w_sh_1_iter_conv_init_m	.343
82	compact_resnet50_robust_IT	.342
83	cvt_cvt-21-224-in1k_4_LucyV4	.342
84	0.5x_resnet-18_LC	.342
85	mobilenet_v2_1.0_224-tf	.342
86	ReAlnet02_ALL	.342
87	resnet-101_v1-tf	.341
88	cvt_cvt-21-384-in1k_4_LucyV4	.341
89	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.341
90	CORnet-Z	.340
91	CORnet-S	.340
92	mobilenet_v2_1_0_224	.339
93	ReAlnet10_ALL	.339
94	ReAlnet01_ALL	.339
95	compact_vgg19_IT	.338
96	ReAlnet01_cornet_fov12	.338
97	cvt_cvt-13-224-in1k_4_LucyV4	.338
98	resnet50-SIN	.338
99	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.337
100	vit_large_patch14_clip_224:openai_ft_in1k	.337
101	ReAlnet03_ALL	.336
102	deit_large_imagenet_full_seed-0	.336
103	resnet50_imagenet_full	.336
104	cv_18_dagger_408_pretrained	.336
105	omnivore_swinB	.336
106	resnet-101_v2-tf	.336
107	ReAlnet06_ALL	.335
108	AT_efficientnet-b2	.335
109	ReAlnet05_ALL	.335
110	resnet-18-LC_d_w_sh_1x1_conv_init_m	.335
111	ReAlnet04_ALL	.335
112	resnet50_simclr	.335
113	grcnn_robust_v1	.334
114	resnet18-colorization	.334
115	omnivore_swinS	.334
116	ReAlnet09_ALL	.333
117	grcnn_v2_text_noise	.332
118	mobilenet_v2_0.75_160-tf	.332
119	resnet-50-pytorch	.332
120	resnet-50-robust	.332
121	convnext_tiny:in12k_ft_in1k	.332
122	resnet50-SIN_IN	.332
123	resnet-50_v2-tf	.331
124	resnet_50_v1_spiking	.331
125	resnet50-sup	.331
126	resnet_50_v1	.331
127	convnext_base:clip_laiona_augreg_ft_in1k_384	.331
128	antialiased-rnext101_32x8d	.331
129	vonegrcnn_47e	.330
130	ReAlnet08_ALL	.330
131	resnet50-VITO-8deg-cc	.330
132	mobilenet_v2_0_75_160	.329
133	Res2Net50_26w_4s	.329
134	resnet_SIN_IN_FT_IN	.329
135	vit_large_patch14_clip_224:laion2b_ft_in1k	.329
136	resnet50_l2_3_robust	.329
137	CLIP-RN50	.328
138	regnet_y_400mf	.328
139	omnivore_swinT	.328
140	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.328
141	alexnet_fov4	.327
142	resnet152_ecoset_full	.326
143	VOneCORnet-S	.326
144	mobilenet_v2_1_0_192	.326
145	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.326
146	grcnn_109	.326
147	nasnet_mobile-tf	.325
148	BiT-S-R50x3	.325
149	mobilenet_v2_1.3_224-tf	.325
150	nasnet_large-tf	.324
151	ReAlnet07_ALL	.324
152	resnet-152_v2-tf	.324
153	mobilenet_v2_1_0_128	.324
154	resnet18-contrastive_predictive	.324
155	densenet-121	.324
156	resnet50_linf_4_robust	.323
157	0.5x_resnet-18_LC_w_sh_100_iter	.322
158	resnet50_random_linf8_perturb	.322
159	resnet50-vitoimagevidnet8	.321
160	mobilenet_v1_0.75_160	.321
161	resnet-18-LC_conv_init_m	.321
162	densenet-121-keras	.321
163	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.320
164	mobilenet_v1_1.0_224	.320
165	mobilenet_v2_1_0_160	.319
166	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.319
167	deit_small_imagenet_full_seed-0	.319
168	AT_efficientnet-b4	.319
169	mobilenet_v2_0.75_192-tf	.318
170	BiT-M-R50x3	.318
171	mobilenet_v2_1_3_224	.318
172	CLIP_ViT-B_32	.317
173	yudixie_resnet50_imagenet1kpret_0_240908	.317
174	yudixie_resnet50_imagenet1kpret_0_240312	.317
175	resnet_50_v1_spiking_l4	.317
176	resnet_50_v1_spiking_l4a	.317
177	resnet50_tutorial	.317
178	mobilenet_v2_0.5_160	.317
179	FrankRobWobv0	.317
180	ViT-B/32	.317
181	texture_shape_resnet50_trained_on_SIN	.316
182	resnet152_imagenet_full	.316
183	AdvProp_efficientnet-b2	.316
184	resnet50	.315
185	0.5x_resnet-18	.315
186	imagenet_l2_3_0	.315
187	mobilenet_v2_1.0_128-tf	.315
188	vgg-19-keras	.315
189	inception_resnet_v2	.315
190	resnet50_imagenet_10_seed-0	.315
191	efficientnet_b2_imagenet_full	.315
192	alexnet_random_l2_3_perturb	.315
193	resnet50_random_l2_perturb	.313
194	resnet50_moco_v2	.313
195	resnet50_ewconplus_wzc	.313
196	effnetv2m_custom384	.312
197	alexnet_l2_3_robust	.312
198	mobilenet_v1_0.25_160	.312
199	resnet-18_test_m	.312
200	resnet-18	.312
201	AT_efficientnet-b7	.312
202	mobilenet_v1_0.75_192	.312
203	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.312
204	mobilenet_v2_0.75_128	.311
205	mobilenet_v1_1.0_160	.311
206	BiT-S-R152x2	.311
207	AdvProp_efficientnet-b4	.311
208	resnet34_ecoset_full	.310
209	vgg-16-keras	.310
210	efficientnet_b0	.310
211	mobilenet_v1_1.0_128	.310
212	resnet-152_v1-tf	.310
213	efficientnet_b0_imagenet_full	.310
214	yudixie_resnet18_imagenet1kpret_0_240719	.310
215	resnet18_ecoset_full	.309
216	mobilenet_v2_0.75_224-tf	.309
217	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.308
218	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.308
219	AdvProp_efficientnet-b7	.308
220	mobilenet_v2_0.35_96	.307
221	inception_v3-tf	.307
222	mobilenet_v1_0.75_224	.306
223	resnet50_linf_8_robust	.306
224	ReAlnet01_cornet_fov16	.306
225	mobilenet_v1_0.5_224	.305
226	mobilenet_v2_1.0_192-tf	.305
227	convnext_small_imagenet_100_seed-0	.305
228	convnext_large:fb_in22k_ft_in1k	.304
229	mobilenet_v2_0_75_224	.304
230	mobilenet_v1_1.0_192	.304
231	alexnet	.304
232	ReAlnet01_cornet_fov4	.303
233	RN50	.303
234	antialias-resnet152	.303
235	xception-keras	.303
236	vit_base_patch16_clip_224:openai_ft_in1k	.302
237	resnet_50_v2	.301
238	alexnet_random_linf8_perturb	.301
239	resnet34_imagenet_full	.301
240	alexnet_reduced_aliasing_early_checkpoint	.301
241	AdvProp_efficientnet-b6	.301
242	mobilenet_v1_0.5_160	.300
243	mobilenet_v2_0.5_128	.300
244	mobilenet_v2_0.5_192-tf	.300
245	resnet101	.299
246	resnet101_imagenet_full	.299
247	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.298
248	mobilenet_v2_0.35_160	.298
249	resnet_101_v2	.298
250	efficientnet-b7	.298
251	AdvProp_efficientnet-b0	.298
252	BiT-S-R50x1	.297
253	vonealexnet_gaussian_noise_std4_fixed	.297
254	mobilenet_v2_0_5_192	.296
255	vgg_16	.296
256	mobilenet_v2_1.0_160-tf	.296
257	densenet-169	.296
258	focalnet_tiny_lrf_in1k	.294
259	effnetb1_272x240	.294
260	squeezenet1_1	.293
261	resnet18_imagenet_full	.293
262	BiT-S-R101x3	.293
263	CLIP_resnet50	.292
264	CLIP_resnet50_float32	.292
265	inception_v3	.292
266	AlexNet_SIN	.291
267	inception_v2-tf	.290
268	r3m_resnet34	.290
269	densenet-169-keras	.290
270	mobilenet_v1_0.75_128	.290
271	resnet_50_v1_spiking_l3	.289
272	mobilenet_v2_0_75_192	.289
273	mobilenet_v2_0.35_128	.289
274	yolos_tiny	.288
275	resnext101_32x16d_wsl	.288
276	r3m_resnet18	.287
277	resnet50_byol	.287
278	mobilenet_v2_0.5_224-tf	.287
279	SWSL_resnet50	.287
280	mobilenet_v2_0.35_224	.286
281	resnet18-contrastive_multiview	.286
282	resnext101_32x48d_wsl	.285
283	pnasnet_large-tf	.285
284	resnet18-supervised	.282
285	convnext_femto_ols:d1_in1k	.282
286	mobilenet_v1_0.5_192	.282
287	mobilenet_v2_0.5_96	.281
288	mobilenet_v2_0.75_96	.281
289	fixres_resnext101_32x48d_wsl	.280
290	resnet18-deepcluster	.280
291	BiT-M-R50x1	.279
292	BiT-M-R152x4	.278
293	resnet18-relative_position	.277
294	convnext_tiny_sup	.276
295	BiT-S-R101x1	.276
296	AdvProp_efficientnet-b8	.276
297	resnext101_32x32d_wsl	.275
298	blt_vs	.275
299	mobilenet_v1_0.5_128	.275
300	resnet18_imagenet21kP	.275
301	alexnet_ks_torevert	.274
302	alexnet	.274
303	alexnet	.274
304	alexnet	.274
305	alexnet-baseline	.274
306	alexnet	.274
307	alexnet	.274
308	alexnet	.274
309	alexnet	.274
310	alexnet_workflow_trigger	.274
311	alexnet	.274
312	alexnet	.274
313	vit_large_patch14_clip_336:laion2b_ft_in1k	.273
314	yudixie_resnet50_object_class_0_240908	.273
315	imagenet_l2_10_0	.273
316	BiT-M-R101x3	.273
317	BiT-M-R152x2	.272
318	mobilenet_v1_0.25_192	.271
319	mobilenet_v2_0.35_192	.271
320	r3m_resnet50_nocrop	.270
321	r3m_resnet50	.269
322	RN50	.269
323	AlexNet_SIN_fov4	.269
324	mobilenet_v2_0_5_224	.268
325	texture_shape_alexnet_trained_on_SIN	.268
326	alexnet_linf_8_robust	.268
327	ReAlnet06	.268
328	resnet-34	.266
329	vit_base_patch14_dinov2:lvd142m	.266
330	alexnet_fov12	.265
331	artResNet18_1	.265
332	deit_small_imagenet_100_seed-0	.264
333	ReAlnet09	.264
334	ReAlnet08	.263
335	alexnet_early_checkpoint	.263
336	mobilenet_v1_0.25_224	.261
337	ReAlnet01	.260
338	SWSL_resnext101_32x8d	.258
339	ReAlnet02	.258
340	briaai_rmbg_1_4	.258
341	ReAlnet05	.254
342	mobilenet_v2_1.0_96	.252
343	vgg_19	.252
344	ReAlnet07	.251
345	alexnet_robust_correct	.249
346	BiT-M-R101x1	.249
347	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.248
348	ReAlnet10	.247
349	ReAlnet04	.246
350	alexnet_fov16	.246
351	inception_v4-tf	.244
352	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.244
353	AlexNet_SIN_fov16	.241
354	ReAlnet03	.236
355	my-model	.235
356	yudixie_resnet50_distance_reg_0_240908	.234
357	squeezenet1_0	.232
358	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.229
359	AlexNet_SIN_fov12	.229
360	yudixie_resnet50_translation_rotation_0_240908	.229
361	cornet_s	.225
362	yudixie_resnet50_category_class_0_240908	.223
363	yudixie_resnet18_object_class_0_240719	.221
364	vit_base_patch14_reg4_dinov2:lvd142m	.219
365	yudixie_resnet18_category_class_0_240719	.219
366	vit_base_patch16_dinov3:lvd1689m	.215
367	mobilenet_v1_0.25_128	.214
368	prednet	.211
369	yudixie_resnet50_distance_rotation_0_240908	.209
370	yudixie_resnet50_distance_translation_0_240908	.207
371	vggface	.206
372	yudixie_resnet50_distance_translation_rotation_0_240908	.205
373	resnet-152_v2_pytorch	.200
374	yudixie_resnet50_translation_reg_0_240908	.199
375	compact_resnet50_V4	.195
376	resnet18-depth_prediction	.195
377	resnet50_primary_visual_cortex	.192
378	resnet50	.192
379	yudixie_resnet50_rotation_reg_0_240908	.190
380	compact_resnet50_robust_V4	.188
381	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.186
382	CORnetZ_CIFAR10	.184
383	compact_vgg19_V4	.183
384	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.182
385	yudixie_resnet18_distance_translation_0_240719	.181
386	compact_cornets_V4	.175
387	yudixie_resnet18_distance_translation_rotation_0_240719	.166
388	alexnet_training_seed_08	.164
389	resnet50_imagenet_1_seed-0	.163
390	alexnet_training_seed_01_fov4	.163
391	alexnet_training_seed_02	.162
392	v1-pyr-nodown	.162
393	alexnet_training_seed_09	.157
394	alexnet_training_seed_07	.157
395	yudixie_resnet18_distance_rotation_0_240719	.156
396	resnet50-cifar	.154
397	alexnet_training_seed_10	.153
398	yudixie_resnet18_translation_rotation_0_240719	.152
399	alexnet_training_seed_01	.150
400	yudixie_resnet18_distance_reg_0_240719	.150
401	alexnet_training_seed_05	.148
402	yudixie_resnet18_rotation_reg_0_240719	.146
403	resnet50-meshes-lt-100-original-scratch	.140
404	alexnet_training_seed_01_fov12	.139
405	resnet-50_untrained	.139
406	mobilevit_small	.137
407	alexnet_training_seed_04	.134
408	resnet50_FractalDB	.133
409	alexnet_training_seed_06	.133
410	alexnet_training_seed_01_fov16	.133
411	yudixie_resnet18_translation_reg_0_240719	.132
412	resnet-18_untrained	.131
413	resnet-50x2_untrained	.129
414	yudixie_resnet18_random_0_240719	.126
415	resnet50_pretrained_with_retinal_waves	.122
416	resnet18-autoencoder	.118
417	yudixie_resnet50_random_0_240908	.117
418	convnext_small_imagenet_10_seed-0	.116
419	resnet50-meshes-lt-100-original-pretrained	.090
420	CORnetZ_CIFAR10_bs32_20_04	.084
421	fitvid_trained_on_physion	.066
422	resnet-18-LC_untrained	.063
423	convnext_small_imagenet_1_seed-0	.047
424	deit_small_imagenet_10_seed-0	.027
425	deit_small_imagenet_1_seed-0	.027
426	my-model	.013
427	pixels	.012

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