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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	vit_large_clip336_openai	.372
22	convnext_small_imagenet_full_seed-0	.372
23	resnet-18-LC_w_sh_100_iter_m	.372
24	resnet50-vicregl0p9	.371
25	convnext_tiny_imagenet_full_seed-0	.371
26	resnet50_robust_l2_eps3	.370
27	eBarlow_lmda_02_1000ep	.369
28	resnet-18-LC_m	.369
29	resnet50-vicregl0p75	.368
30	vonegrcnn_62e_nobn	.367
31	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.367
32	vision_transformer_vit_large_patch16_224	.367
33	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.367
34	ReAlnet01_cornet	.367
35	resnet50_simclr_linhead_01norm	.366
36	voneresnet-50	.366
37	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.366
38	convnext_xlarge:fb_in22k_ft_in1k	.365
39	ReAlnet03_cornet	.365
40	convnext_large_imagenet_full_seed-0	.365
41	resnet50-moclr8deg	.365
42	vonegrcnn_52e_full	.364
43	vit_relpos_base_patch16_clsgap_224:sw_in1k	.364
44	ReAlnet02_cornet	.364
45	resnet-18-LC_w_sh_100_iter_conv_init_m	.363
46	resnet50_simsiam_linhead	.362
47	inception_v1-tf	.362
48	resnet50-SIN_IN_IN	.360
49	resnet50_imagenet_100_seed-0	.360
50	nasnet_mobile	.359
51	convnext_base_imagenet_full_seed-0	.359
52	ReAlnet04_cornet	.359
53	ReAlnet05_cornet	.358
54	resnet18-local_aggregation	.358
55	densenet-201	.358
56	compact_resnet50_IT	.357
57	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.357
58	ReAlnet06_cornet	.357
59	ReAlnet09_cornet	.356
60	mobilenet_v2_1-4_224_pytorch	.356
61	resnet-50_v1-tf	.356
62	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.356
63	vit_huge_clip336_laion	.355
64	compact_cornets_IT	.355
65	cvt_cvt-13-384-in1k_4_LucyV4	.354
66	0.5x_resnet-18_LC_w_sh_1_iter	.352
67	mobilenet_v2_1.4_224-tf	.352
68	resnet-18-LC_w_sh_1_iter_m	.351
69	antialiased-r50	.351
70	grcnn	.351
71	ViT_L_32_imagenet1k	.351
72	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.350
73	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.350
74	deit3_base_patch16_224_fb_in1k	.350
75	efficientnet_b1_imagenet_full	.350
76	resnet101_ecoset_full	.350
77	densenet-201-keras	.349
78	0.5x_resnet-18_LC_w_sh_10_iter	.349
79	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.348
80	resnet50_vicreg_linhead	.348
81	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.347
82	mobilenet_v2_1_4_224	.347
83	inception_v1	.346
84	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.346
85	resnet50_ecoset_full	.345
86	voneresnet-50-non_stochastic	.345
87	BiT-S-R152x4	.344
88	shufflenet_v2_x1_0	.343
89	resnet-18-LC_w_sh_1_iter_conv_init_m	.343
90	compact_resnet50_robust_IT	.342
91	dinov2_vitg14_lc	.342
92	cvt_cvt-21-224-in1k_4_LucyV4	.342
93	0.5x_resnet-18_LC	.342
94	resnet50_ewconplus_wzc_seed2_2__323	.342
95	convnext_large_clip_laion2b_finelayers	.342
96	mobilenet_v2_1.0_224-tf	.342
97	ReAlnet02_ALL	.342
98	resnet-101_v1-tf	.341
99	cvt_cvt-21-384-in1k_4_LucyV4	.341
100	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.341
101	CORnet-Z	.340
102	resnet50_hvs_wzc	.340
103	CORnet-S	.340
104	mobilenet_v2_1_0_224	.339
105	ReAlnet10_ALL	.339
106	ReAlnet01_ALL	.339
107	resnet50_barlowtwins_linhead	.339
108	compact_vgg19_IT	.338
109	ReAlnet01_cornet_fov12	.338
110	cvt_cvt-13-224-in1k_4_LucyV4	.338
111	resnet50-SIN	.338
112	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.337
113	vit_large_patch14_clip_224:openai_ft_in1k	.337
114	ReAlnet03_ALL	.336
115	deit_large_imagenet_full_seed-0	.336
116	resnet50_imagenet_full	.336
117	cv_18_dagger_408_pretrained	.336
118	omnivore_swinB	.336
119	resnet-101_v2-tf	.336
120	convnext_xxlarge_clip	.336
121	ReAlnet06_ALL	.335
122	AT_efficientnet-b2	.335
123	ReAlnet05_ALL	.335
124	resnet-18-LC_d_w_sh_1x1_conv_init_m	.335
125	ReAlnet04_ALL	.335
126	mehrer2020_alexnet_training_seed_10	.335
127	resnet50_simclr	.335
128	resnet50_byol_linhead	.334
129	grcnn_robust_v1	.334
130	resnet50_ewconplus_wzc_seed5_2__323	.334
131	resnet18-colorization	.334
132	dinov2_vitg14_reg_lc	.334
133	omnivore_swinS	.334
134	ReAlnet09_ALL	.333
135	grcnn_v2_text_noise	.332
136	mobilenet_v2_0.75_160-tf	.332
137	resnet-50-pytorch	.332
138	resnet-50-robust	.332
139	convnext_tiny:in12k_ft_in1k	.332
140	resnet50-SIN_IN	.332
141	resnet-50_v2-tf	.331
142	resnet_50_v1_spiking	.331
143	resnet50-sup	.331
144	resnet_50_v1	.331
145	convnext_base:clip_laiona_augreg_ft_in1k_384	.331
146	antialiased-rnext101_32x8d	.331
147	vonegrcnn_47e	.330
148	ReAlnet08_ALL	.330
149	resnet50-VITO-8deg-cc	.330
150	mobilenet_v2_0_75_160	.329
151	Res2Net50_26w_4s	.329
152	resnet_SIN_IN_FT_IN	.329
153	vit_large_patch14_clip_224:laion2b_ft_in1k	.329
154	resnet50_l2_3_robust	.329
155	mehrer2020_alexnet_training_seed_01	.328
156	CLIP-RN50	.328
157	regnet_y_400mf	.328
158	omnivore_swinT	.328
159	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.328
160	alexnet_fov4	.327
161	resnet152_ecoset_full	.326
162	VOneCORnet-S	.326
163	deit3_base_patch16_224_fb_in22k_ft_in1k	.326
164	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.326
165	mobilenet_v2_1_0_192	.326
166	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.326
167	grcnn_109	.326
168	mehrer2020_alexnet_training_seed_04	.326
169	nasnet_mobile-tf	.325
170	BiT-S-R50x3	.325
171	mobilenet_v2_1.3_224-tf	.325
172	nasnet_large-tf	.324
173	ReAlnet07_ALL	.324
174	resnet-152_v2-tf	.324
175	mobilenet_v2_1_0_128	.324
176	resnet18-contrastive_predictive	.324
177	densenet-121	.324
178	resnet50_linf_4_robust	.323
179	0.5x_resnet-18_LC_w_sh_100_iter	.322
180	resnet50_random_linf8_perturb	.322
181	resnet50-vitoimagevidnet8	.321
182	mobilenet_v1_0.75_160	.321
183	resnet-18-LC_conv_init_m	.321
184	densenet-121-keras	.321
185	mehrer2020_alexnet_training_seed_06	.321
186	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.320
187	resnet50_ewconplus_wzc_seed6_2_323	.320
188	dinov2_vitl14_reg_lc	.320
189	dinov2_vitl14_reg_lc_featread	.320
190	mobilenet_v1_1.0_224	.320
191	mobilenet_v2_1_0_160	.319
192	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.319
193	deit_small_imagenet_full_seed-0	.319
194	AT_efficientnet-b4	.319
195	mobilenet_v2_0.75_192-tf	.318
196	BiT-M-R50x3	.318
197	mobilenet_v2_1_3_224	.318
198	CLIP_ViT-B_32	.317
199	yudixie_resnet50_imagenet1kpret_0_240908	.317
200	yudixie_resnet50_imagenet1kpret_0_240312	.317
201	resnet_50_v1_spiking_l4	.317
202	resnet_50_v1_spiking_l4a	.317
203	resnet50_tutorial	.317
204	mobilenet_v2_0.5_160	.317
205	FrankRobWobv0	.317
206	ViT-B/32	.317
207	texture_shape_resnet50_trained_on_SIN	.316
208	resnet152_imagenet_full	.316
209	AdvProp_efficientnet-b2	.316
210	resnet50	.315
211	0.5x_resnet-18	.315
212	imagenet_l2_3_0	.315
213	mobilenet_v2_1.0_128-tf	.315
214	vgg-19-keras	.315
215	resnet50_st_wzc_2	.315
216	inception_resnet_v2	.315
217	resnet50_imagenet_10_seed-0	.315
218	mehrer2020_alexnet_training_seed_07	.315
219	efficientnet_b2_imagenet_full	.315
220	alexnet_random_l2_3_perturb	.315
221	resnet50_random_l2_perturb	.313
222	resnet50_moco_v2	.313
223	resnet50_ewconplus_wzc	.313
224	effnetv2m_custom384	.312
225	alexnet_l2_3_robust	.312
226	mobilenet_v1_0.25_160	.312
227	resnet-18_test_m	.312
228	resnet-18	.312
229	AT_efficientnet-b7	.312
230	mobilenet_v1_0.75_192	.312
231	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.312
232	mobilenet_v2_0.75_128	.311
233	mobilenet_v1_1.0_160	.311
234	BiT-S-R152x2	.311
235	AdvProp_efficientnet-b4	.311
236	resnet34_ecoset_full	.310
237	vgg-16-keras	.310
238	efficientnet_b0	.310
239	mobilenet_v1_1.0_128	.310
240	resnet-152_v1-tf	.310
241	efficientnet_b0_imagenet_full	.310
242	yudixie_resnet18_imagenet1kpret_0_240719	.310
243	yudixie_wbh_object_class_scaling_0415_imagenet	.310
244	resnet50_st_wzc_seed3_2_323	.309
245	resnet18_ecoset_full	.309
246	mehrer2020_alexnet_training_seed_08	.309
247	mobilenet_v2_0.75_224-tf	.309
248	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.308
249	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.308
250	AdvProp_efficientnet-b7	.308
251	mobilenet_v2_0.35_96	.307
252	inception_v3-tf	.307
253	mobilenet_v1_0.75_224	.306
254	mehrer2020_alexnet_training_seed_01_fov12	.306
255	resnet50_linf_8_robust	.306
256	ReAlnet01_cornet_fov16	.306
257	mobilenet_v1_0.5_224	.305
258	mobilenet_v2_1.0_192-tf	.305
259	convnext_small_imagenet_100_seed-0	.305
260	convnext_large:fb_in22k_ft_in1k	.304
261	mobilenet_v2_0_75_224	.304
262	mobilenet_v1_1.0_192	.304
263	ReAlnet01_cornet_fov4	.303
264	RN50	.303
265	antialias-resnet152	.303
266	xception-keras	.303
267	mehrer2020_alexnet_training_seed_05	.302
268	vit_base_patch16_clip_224:openai_ft_in1k	.302
269	dinov2_vitl14_lc_res336	.302
270	resnet_50_v2	.301
271	alexnet_random_linf8_perturb	.301
272	resnet34_imagenet_full	.301
273	alexnet_reduced_aliasing_early_checkpoint	.301
274	AdvProp_efficientnet-b6	.301
275	seresnext50_32x4d	.300
276	mobilenet_v1_0.5_160	.300
277	mobilenet_v2_0.5_128	.300
278	dinov2_vitl14_lc	.300
279	mobilenet_v2_0.5_192-tf	.300
280	resnet101	.299
281	resnet101_imagenet_full	.299
282	mehrer2020_alexnet_training_seed_09	.299
283	resnet50_st_wzc_seed7_2_323	.299
284	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.298
285	mobilenet_v2_0.35_160	.298
286	resnet_101_v2	.298
287	efficientnet-b7	.298
288	AdvProp_efficientnet-b0	.298
289	BiT-S-R50x1	.297
290	vonealexnet_gaussian_noise_std4_fixed	.297
291	mobilenet_v2_0_5_192	.296
292	resnet50_st_wzc_seed6_2_323	.296
293	vgg_16	.296
294	mobilenet_v2_1.0_160-tf	.296
295	densenet-169	.296
296	focalnet_tiny_lrf_in1k	.294
297	effnetb1_272x240	.294
298	squeezenet1_1	.293
299	resnet18_imagenet_full	.293
300	deepeisnn_ei_imagenet_resnet18	.293
301	BiT-S-R101x3	.293
302	CLIP_resnet50	.292
303	CLIP_resnet50_float32	.292
304	inception_v3	.292
305	AlexNet_SIN	.291
306	inception_v2-tf	.290
307	r3m_resnet34	.290
308	densenet-169-keras	.290
309	mobilenet_v1_0.75_128	.290
310	resnet_50_v1_spiking_l3	.289
311	mobilenet_v2_0_75_192	.289
312	mehrer2020_alexnet_training_seed_02	.289
313	mobilenet_v2_0.35_128	.289
314	mehrer2020_alexnet_training_seed_03	.288
315	yolos_tiny	.288
316	resnext101_32x16d_wsl	.288
317	r3m_resnet18	.287
318	resnet50_byol	.287
319	mobilenet_v2_0.5_224-tf	.287
320	SWSL_resnet50	.287
321	mobilenet_v2_0.35_224	.286
322	eva02_large_in22k	.286
323	resnet18-contrastive_multiview	.286
324	resnext101_32x48d_wsl	.285
325	pnasnet_large-tf	.285
326	eicircuit_resnet18_bn_20260919	.284
327	resnet18-supervised	.282
328	convnext_femto_ols:d1_in1k	.282
329	mobilenet_v1_0.5_192	.282
330	mehrer2020_alexnet_training_seed_01_fov4	.281
331	mobilenet_v2_0.5_96	.281
332	mobilenet_v2_0.75_96	.281
333	fixres_resnext101_32x48d_wsl	.280
334	resnet18-deepcluster	.280
335	BiT-M-R50x1	.279
336	BiT-M-R152x4	.278
337	resnet18-relative_position	.277
338	convnext_tiny_sup	.276
339	BiT-S-R101x1	.276
340	AdvProp_efficientnet-b8	.276
341	resnext101_32x32d_wsl	.275
342	blt_vs	.275
343	mobilenet_v1_0.5_128	.275
344	resnet18_imagenet21kP	.275
345	alexnet_ks_torevert	.274
346	alexnet	.274
347	vit_large_patch14_clip_336:laion2b_ft_in1k	.273
348	yudixie_resnet50_object_class_0_240908	.273
349	imagenet_l2_10_0	.273
350	BiT-M-R101x3	.273
351	BiT-M-R152x2	.272
352	resnet18_fair	.271
353	mobilenet_v1_0.25_192	.271
354	mobilenet_v2_0.35_192	.271
355	r3m_resnet50_nocrop	.270
356	r3m_resnet50	.269
357	RN50	.269
358	AlexNet_SIN_fov4	.269
359	mobilenet_v2_0_5_224	.268
360	texture_shape_alexnet_trained_on_SIN	.268
361	alexnet_linf_8_robust	.268
362	ReAlnet06	.268
363	pr1_stl10_disentangled_alpha04	.267
364	resnet-34	.266
365	vit_base_patch14_dinov2-lvd142m	.266
366	alexnet_fov12	.265
367	artResNet18_1	.265
368	deit_small_imagenet_100_seed-0	.264
369	ReAlnet09	.264
370	ReAlnet08	.263
371	alexnet_early_checkpoint	.263
372	regnety_032	.261
373	mobilenet_v1_0.25_224	.261
374	pnasnet_large_halfPrecision	.261
375	ReAlnet01	.260
376	SWSL_resnext101_32x8d	.258
377	ReAlnet02	.258
378	briaai_rmbg_1_4	.258
379	ReAlnet05	.254
380	mobilenet_v2_1.0_96	.252
381	vgg_19	.252
382	ReAlnet07	.251
383	alexnet_robust_correct	.249
384	BiT-M-R101x1	.249
385	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.248
386	ReAlnet10	.247
387	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.246
388	ReAlnet04	.246
389	alexnet_fov16	.246
390	inception_v4-tf	.244
391	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.244
392	AlexNet_SIN_fov16	.241
393	ReAlnet03	.236
394	my-model	.235
395	yudixie_resnet50_distance_reg_0_240908	.234
396	squeezenet1_0	.232
397	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.229
398	AlexNet_SIN_fov12	.229
399	yudixie_resnet50_translation_rotation_0_240908	.229
400	mehrer2020_alexnet_training_seed_01_fov16	.228
401	cornet_s	.225
402	yudixie_resnet50_category_class_0_240908	.223
403	convnext_base_fb_in1k_gram_aligned_dinov3	.222
404	yudixie_resnet18_object_class_0_240719	.221
405	vit_base_patch14_reg4_dinov2-lvd142m	.219
406	yudixie_resnet18_category_class_0_240719	.219
407	vit_base_patch16_dinov3-lvd1689m	.215
408	mobilenet_v1_0.25_128	.214
409	ijepa_vith14_linhead	.214
410	prednet	.211
411	yudixie_resnet50_distance_rotation_0_240908	.209
412	yudixie_resnet50_distance_translation_0_240908	.207
413	vggface	.206
414	yudixie_resnet50_distance_translation_rotation_0_240908	.205
415	resnet-152_v2_pytorch	.200
416	yudixie_resnet50_translation_reg_0_240908	.199
417	compact_resnet50_V4	.195
418	resnet18-depth_prediction	.195
419	resnet50_primary_visual_cortex	.192
420	yudixie_resnet50_rotation_reg_0_240908	.190
421	compact_resnet50_robust_V4	.188
422	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.186
423	CORnetZ_CIFAR10	.184
424	compact_vgg19_V4	.183
425	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.182
426	yudixie_resnet18_distance_translation_0_240719	.181
427	deepeisnn_ei_cifar10_resnet18	.181
428	compact_cornets_V4	.175
429	alexnet_training_seed_03	.174
430	deepeisnn_ei_cifar10_vgg19	.173
431	yudixie_resnet18_distance_translation_rotation_0_240719	.166
432	alexnet_training_seed_08	.164
433	resnet50_imagenet_1_seed-0	.163
434	alexnet_training_seed_01_fov4	.163
435	alexnet_training_seed_02	.162
436	v1-pyr-nodown	.162
437	alexnet_training_seed_09	.157
438	alexnet_training_seed_07	.157
439	yudixie_resnet18_distance_rotation_0_240719	.156
440	resnet50-cifar	.154
441	alexnet_training_seed_10	.153
442	yudixie_resnet18_translation_rotation_0_240719	.152
443	alexnet_training_seed_01	.150
444	yudixie_resnet18_distance_reg_0_240719	.150
445	alexnet_training_seed_05	.148
446	yudixie_resnet18_rotation_reg_0_240719	.146
447	predictive_coding_pc	.146
448	gabor_filter_mean_abs_4x4_v2	.140
449	alexnet_training_seed_01_fov12	.139
450	resnet-50_untrained	.139
451	mobilevit_small	.137
452	yudixie_wbh_object_class_scaling_0415_run_0	.136
453	alexnet_training_seed_04	.134
454	resnet50_FractalDB	.133
455	alexnet_training_seed_06	.133
456	alexnet_training_seed_01_fov16	.133
457	yudixie_resnet18_translation_reg_0_240719	.132
458	convnext_large_in22k_supervised	.131
459	resnet-18_untrained	.131
460	resnet-50x2_untrained	.129
461	yudixie_resnet18_random_0_240719	.126
462	convnext_base_fb_in22k_ft_in1k	.124
463	yudixie_wbh_object_class_scaling_0415_run_2	.123
464	resnet50_pretrained_with_retinal_waves	.122
465	resnet18-autoencoder	.118
466	yudixie_resnet50_random_0_240908	.117
467	convnext_small_imagenet_10_seed-0	.116
468	gabor_filter_entropy_4x4_v2	.109
469	gabor_filter_entropy_4x4_v2_forcedCosine	.105
470	yudixie_wbh_object_class_scaling_0415_run_3	.102
471	gabor_filter_entropy_4x4	.101
472	convnext_base_fb_in1k	.100
473	yudixie_wbh_object_class_scaling_0415_run_1	.090
474	CORnetZ_CIFAR10_bs32_20_04	.084
475	hmax	.069
476	fitvid_trained_on_physion	.066
477	resnet-18-LC_untrained	.063
478	convnext_small_imagenet_1_seed-0	.047
479	deit_small_imagenet_10_seed-0	.027
480	deit_small_imagenet_1_seed-0	.027
481	my-model	.013
482	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