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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Sanghavi2020.V4-pls")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	ReAlnet01_cornet_fov4	.623
2	mehrer2020_alexnet_training_seed_01_fov4	.616
3	alexnet_fov4	.613
4	compact_resnet50_robust_V4	.601
5	custom_model_cv_18_dagger_408	.595
6	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.591
7	AdvProp_efficientnet-b4	.590
8	dinov2_vitg14_lc	.589
9	densenet-169-keras	.589
10	dinov2_vitg14_reg_lc	.589
11	densenet-121-keras	.589
12	resnet50	.589
13	ReAlnet07_cornet	.588
14	ReAlnet08_cornet	.587
15	ReAlnet02_cornet	.587
16	compact_resnet50_V4	.586
17	resnet50_ewconplus_wzc_seed2_2__323	.585
18	ReAlnet10_cornet	.585
19	yudixie_resnet50_imagenet1kpret_0_240908	.584
20	resnet_50_v1	.584
21	resnet50-sup	.584
22	resnet_50_v1_spiking	.584
23	resnet_50_v1_spiking_l4	.584
24	resnet_50_v1_spiking_l4a	.584
25	resnet50_tutorial	.584
26	resnet_50_v1_spiking_l3	.584
27	yudixie_resnet50_imagenet1kpret_0_240312	.584
28	ReAlnet03_cornet	.584
29	ReAlnet05_cornet	.583
30	efficientnet_b1_imagenet_full	.583
31	ReAlnet04_cornet	.583
32	densenet-201-keras	.582
33	ReAlnet09_cornet	.582
34	antialiased-r50	.582
35	vit_large_clip336_openai	.581
36	antialiased-rnext101_32x8d	.581
37	resnet50_ewconplus_wzc_seed6_2_323	.581
38	resnet50_ewconplus_wzc_seed5_2__323	.581
39	resnet50_random_linf8_perturb	.581
40	efficientnet_b2_imagenet_full	.581
41	SWSL_resnet50	.580
42	resnet34_ecoset_full	.580
43	focalnet_tiny_lrf_in1k	.580
44	ReAlnet06_cornet	.580
45	resnet50_random_l2_perturb	.580
46	resnet50-SIN_IN_IN	.579
47	resnet_SIN_IN_FT_IN	.579
48	resnet18-colorization	.579
49	ReAlnet01_cornet	.579
50	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.578
51	deit3_base_patch16_224_fb_in1k	.578
52	resnet-50_v1-tf	.578
53	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.578
54	inception_v1-tf	.577
55	deit3_base_patch16_224_fb_in22k_ft_in1k	.576
56	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.576
57	resnet50-SIN_IN	.576
58	resnet-101_v1-tf	.576
59	resnet50_linf_4_robust	.576
60	AdvProp_efficientnet-b8	.575
61	effnetv2m_custom384	.575
62	xception-keras	.575
63	ReAlnet02_ALL	.575
64	resnext101_32x8d_wsl	.575
65	ReAlnet01_ALL	.575
66	ReAlnet08_ALL	.575
67	ReAlnet09_ALL	.574
68	resnet-152_v1-tf	.574
69	vgg_16	.574
70	vonegrcnn_62e_nobn	.574
71	ReAlnet07_ALL	.574
72	resnet-18-LC_w_sh_100_iter_conv_init_m	.574
73	ReAlnet06_ALL	.574
74	vgg-16-keras	.574
75	vit_base_patch16_clip_224:openai_ft_in1k	.574
76	vonegrcnn_52e_full	.574
77	resnext101_32x16d_wsl	.574
78	resnet152_imagenet_full	.574
79	vision_transformer_vit_large_patch16_224	.574
80	ReAlnet04_ALL	.574
81	deit_large_imagenet_full_seed-0	.574
82	ReAlnet03_ALL	.574
83	BiT-M-R101x3	.573
84	vonegrcnn_47e	.573
85	ReAlnet10_ALL	.573
86	resnet-50_v2-tf	.573
87	ReAlnet05_ALL	.573
88	resnet50_ewconplus_wzc	.573
89	resnet152_ecoset_full	.572
90	resnet-18-LC_d_w_sh_1x1_conv_init_m	.572
91	effnetb1_272x240	.572
92	AdvProp_efficientnet-b6	.572
93	resnet50_imagenet_100_seed-0	.572
94	BiT-S-R101x3	.571
95	omnivore_swinB	.571
96	Res2Net50_26w_4s	.571
97	resnet50_hvs_wzc	.571
98	resnet101_ecoset_full	.571
99	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.571
100	AT_efficientnet-b7	.570
101	resnet18_imagenet_full	.570
102	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.570
103	voneresnet-50	.570
104	resnet50_l2_3_robust	.570
105	0.5x_resnet-18_LC_w_sh_10_iter	.569
106	compact_vgg19_V4	.569
107	AdvProp_efficientnet-b7	.569
108	resnet18_imagenet21kP	.569
109	yudixie_resnet18_imagenet1kpret_0_240719	.569
110	yudixie_wbh_object_class_scaling_0415_imagenet	.569
111	convnext_xxlarge_clip	.569
112	inception_resnet_v2	.568
113	resnet18_ecoset_full	.568
114	regnety_032	.568
115	konkle_alexnetgn_ipcl_ref01_primary_model	.568
116	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.568
117	inception_v2-tf	.568
118	dinov2_vitl14_reg_lc	.568
119	dinov2_vitl14_reg_lc_featread	.568
120	voneresnet-50-robust	.568
121	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.568
122	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.567
123	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.567
124	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.567
125	AdvProp_efficientnet-b2	.567
126	mobilenet_v1_1.0_160	.567
127	convnext_tiny_imagenet_full_seed-0	.567
128	AdvProp_efficientnet-b0	.567
129	resnext101_32x48d_wsl	.567
130	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.567
131	efficientnet_b0_imagenet_full	.567
132	efficientnet_b0	.566
133	AT_efficientnet-b2	.566
134	mobilenet_v2_1_4_224	.566
135	resnet101_imagenet_full	.566
136	BiT-M-R152x2	.566
137	texture_shape_resnet50_trained_on_SIN	.566
138	resnet34_imagenet_full	.566
139	resnet-18-LC_w_sh_100_iter_m	.565
140	SWSL_resnext101_32x8d	.565
141	resnet-18-LC_w_sh_1_iter_m	.565
142	convnext_small_imagenet_full_seed-0	.565
143	omnivore_swinS	.565
144	resnet50_imagenet_full	.565
145	convnext_base_imagenet_full_seed-0	.565
146	resnet-152_v2-tf	.565
147	antialias-resnet152	.564
148	CORnet-S	.564
149	compact_resnet50_IT	.564
150	eicircuit_resnet18_bn_20260919	.564
151	cv_18_dagger_408_pretrained	.564
152	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.564
153	dinov2_vitl14_lc	.563
154	BiT-S-R50x3	.563
155	omnivore_swinT	.563
156	resnet50_robust_l2_eps1	.563
157	BiT-M-R152x4	.563
158	resnet101	.563
159	resnet50_st_wzc_seed6_2_323	.563
160	vit_relpos_base_patch16_clsgap_224:sw_in1k	.563
161	dinov2_vitl14_lc_res336	.562
162	resnet-101_v2-tf	.562
163	voneresnet-50-non_stochastic	.562
164	mobilenet_v1_1.0_224	.562
165	CLIP-RN50	.562
166	resnet-18	.562
167	resnet-18-LC_w_sh_1_iter_conv_init_m	.562
168	FrankRobWobv0	.562
169	resnet-18-LC_w_sh_10_iter_conv_init_m	.561
170	convnext_tiny_sup	.561
171	grcnn_v2_text_noise	.561
172	VOneCORnet-S	.561
173	resnet50_moco_v2	.561
174	mobilenet_v2_1.0_128-tf	.561
175	seresnext50_32x4d	.561
176	convnext_femto_ols:d1_in1k	.561
177	BiT-S-R152x2	.561
178	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.561
179	resnet50_st_wzc_seed7_2_323	.561
180	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.560
181	nasnet_mobile	.560
182	BiT-M-R101x1	.560
183	resnext101_32x32d_wsl	.560
184	mobilenet_v2_1_3_224	.559
185	AT_efficientnet-b4	.559
186	resnet50-vicreg	.559
187	densenet-169	.559
188	regnet_y_400mf	.559
189	AlexNet_SIN_fov4	.558
190	barlow-twins-resnet50	.558
191	inception_v3-tf	.558
192	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.558
193	resnet50_st_wzc_2	.558
194	deit_small_imagenet_full_seed-0	.557
195	nasnet_large-tf	.557
196	densenet-201	.557
197	grcnn_109	.557
198	resnet50_ecoset_full	.557
199	resnet50_st_wzc_seed3_2_323	.557
200	resnet50-vicregl0p9	.557
201	BiT-M-R50x1	.556
202	resnet-18_test_m	.556
203	resnet18-local_aggregation	.556
204	mobilenet_v2_1.3_224-tf	.556
205	convnext_large_clip_laion2b_finelayers	.556
206	cvt_cvt-21-384-in1k_4_LucyV4	.555
207	persistence_memory	.555
208	cvt_cvt-13-384-in1k_4_LucyV4	.554
209	resnet50-vicregl0p75	.554
210	resnet50-VITO-8deg-cc	.554
211	pnasnet_large-tf	.554
212	0.5x_resnet-18_LC_w_sh_100_iter	.554
213	grcnn	.554
214	resnet_50_v2	.554
215	tv_efficientnet-b1	.554
216	resnet50-barlow	.553
217	mobilenet_v2_1_0_128	.553
218	alexnet_random_linf8_perturb	.553
219	densenet-121	.553
220	vgg_19	.553
221	inception_v3	.553
222	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.553
223	mobilenet_v1_0.75_128	.553
224	mobilenet_v2_0_75_224	.553
225	RN50	.552
226	convnext_tiny:in12k_ft_in1k	.552
227	alexnet_random_l2_3_perturb	.552
228	deit_base_imagenet_full_seed-0	.552
229	vonealexnet_gaussian_noise_std4_fixed	.552
230	ViT-B/32	.552
231	CLIP_resnet50	.552
232	CLIP_resnet50_float32	.552
233	resnet50_cpc_linhead	.551
234	CLIP_ViT-B_32	.551
235	cornet_s	.551
236	mobilenet_v2_1.4_224-tf	.551
237	mobilenet_v2_1_0_192	.550
238	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.550
239	mobilenet_v2_1.0_160-tf	.550
240	fixres_resnext101_32x48d_wsl	.550
241	cvt_cvt-13-224-in1k_4_LucyV4	.550
242	mobilenet_v1_1.0_192	.550
243	compact_resnet50_robust_IT	.549
244	mobilenet_v2_0.75_224-tf	.549
245	mobilenet_v1_0.75_160	.549
246	mobilenet_v2_1_0_224	.549
247	resnet50-moclr8deg	.549
248	compact_cornets_V4	.549
249	mobilenet_v2_0_75_192	.549
250	grcnn_robust_v1	.549
251	convnext_large_in22k_supervised	.548
252	convnext_large_imagenet_full_seed-0	.548
253	resnet18-instance_recognition	.548
254	BiT-S-R101x1	.548
255	BiT-S-R50x1	.548
256	alexnet	.548
257	alexnet_ks_torevert	.548
258	convnext_xlarge:fb_in22k_ft_in1k	.548
259	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.548
260	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.548
261	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.548
262	convnext_base:clip_laiona_augreg_ft_in1k_384	.547
263	vgg-19-keras	.547
264	BiT-M-R50x3	.547
265	resnet50-simclr-vissl	.546
266	mobilenet_v2_1.0_192-tf	.546
267	mobilenet_v1_1.0_128	.546
268	0.5x_resnet-18_LC_w_sh_1_iter	.546
269	imagenet_l2_3_0	.546
270	0.5x_resnet-18	.546
271	vit_large_patch14_clip_224:openai_ft_in1k	.545
272	mobilenet_v1_0.75_192	.545
273	resnet50-vitoimagevidnet8	.545
274	resnet50_robust_l2_eps3	.545
275	yudixie_resnet50_object_class_0_240908	.544
276	mobilenet_v1_0.75_224	.544
277	resnet50_byol	.544
278	resnet50_byol	.544
279	resnet50-SIN	.544
280	mobilenet_v2_0.75_192-tf	.544
281	cvt_cvt-21-224-in1k_4_LucyV4	.542
282	nasnet_mobile-tf	.542
283	vit_base_patch16_dinov3-lvd1689m	.541
284	efficientnet-b7	.541
285	mobilenet_v2_0.75_160-tf	.541
286	mobilenet_v2_1.0_224-tf	.541
287	inception_v4-tf	.541
288	mobilenet_v2_1_0_160	.541
289	mobilenet_v2_0.75_128	.540
290	mehrer2020_alexnet_training_seed_08	.540
291	squeezenet1_0	.540
292	BiT-S-R152x4	.540
293	yudixie_resnet50_translation_reg_0_240908	.540
294	vit_base_patch14_dinov2-lvd142m	.540
295	yudixie_resnet50_category_class_0_240908	.539
296	CORnet-Z	.539
297	resnet-18-LC_1st_conv_m	.538
298	mobilenet_v2_0_5_192	.538
299	mehrer2020_alexnet_training_seed_02	.538
300	ReAlnet01_cornet_fov12	.538
301	resnet18-relative_position	.537
302	resnet-18-LC_m	.537
303	vit_base_patch14_reg4_dinov2-lvd142m	.537
304	mobilenet_v1_0.5_192	.537
305	resnet-34	.537
306	vit_large_patch14_clip_224:laion2b_ft_in1k	.536
307	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.536
308	mehrer2020_alexnet_training_seed_04	.536
309	mobilenet_v2_0_5_224	.536
310	shufflenet_v2_x1_0	.536
311	squeezenet1_1	.535
312	RN50	.535
313	inception_v1	.535
314	resnet-18-LC_w_sh_10_iter_m	.535
315	resnet18-contrastive_multiview	.535
316	mobilenet_v2_0.5_224-tf	.534
317	mobilenet_v2_0.5_128	.534
318	mehrer2020_alexnet_training_seed_05	.534
319	mehrer2020_alexnet_training_seed_01	.534
320	yudixie_resnet50_distance_translation_0_240908	.534
321	mobilenet_v1_0.25_224	.533
322	mehrer2020_alexnet_training_seed_07	.533
323	mehrer2020_alexnet_training_seed_03	.533
324	mobilenet_v1_0.5_224	.533
325	convnext_small_imagenet_100_seed-0	.532
326	resnet50_linf_8_robust	.532
327	mobilenet_v2_0_75_160	.531
328	yudixie_resnet50_translation_rotation_0_240908	.531
329	yudixie_resnet50_distance_reg_0_240908	.531
330	resnet18-supervised	.531
331	mehrer2020_alexnet_training_seed_06	.531
332	yudixie_resnet50_distance_translation_rotation_0_240908	.531
333	mehrer2020_alexnet_training_seed_09	.531
334	resnet50_simsiam_linhead	.530
335	yudixie_resnet50_distance_rotation_0_240908	.530
336	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.530
337	resnet18_fair	.530
338	mobilenet_v2_1.0_96	.529
339	vit_large_patch14_clip_336:laion2b_ft_in1k	.528
340	mobilenet_v2_0.5_192-tf	.528
341	convnext_large:fb_in22k_ft_in1k	.528
342	mobilenet_v1_0.5_160	.528
343	0.5x_resnet-18_LC	.527
344	resnet-18-LC_conv_init_m	.527
345	ijepa_vith14_linhead	.525
346	resnet50_vicreg_linhead	.525
347	mobilenet_v1_0.5_128	.524
348	mobilenet_v2_0.35_224	.523
349	alexnet_reduced_aliasing_early_checkpoint	.522
350	resnet18-deepcluster	.522
351	resnet50_barlowtwins_linhead	.521
352	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.521
353	resnet50_primary_visual_cortex	.520
354	mobilenet_v2_0.5_160	.520
355	resnet50_simclr	.520
356	r3m_resnet18	.519
357	ReAlnet10	.519
358	r3m_resnet34	.517
359	mobilenet_v2_0.35_192	.517
360	ReAlnet02	.515
361	yudixie_resnet18_category_class_0_240719	.515
362	ReAlnet08	.515
363	alexnet_early_checkpoint	.515
364	mobilenet_v2_0.75_96	.514
365	ReAlnet07	.513
366	resnet50_byol_linhead	.512
367	texture_shape_alexnet_trained_on_SIN	.512
368	mehrer2020_alexnet_training_seed_10	.511
369	ReAlnet03	.510
370	yudixie_resnet50_rotation_reg_0_240908	.510
371	AlexNet_SIN	.509
372	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.509
373	ReAlnet06	.509
374	imagenet_l2_10_0	.509
375	ReAlnet01	.508
376	resnet50_simclr_linhead_01norm	.508
377	deepeisnn_ei_imagenet_resnet18	.508
378	ReAlnet09	.507
379	ReAlnet04	.506
380	mobilenet_v1_0.25_192	.506
381	ReAlnet05	.505
382	mobilenet_v2_0.5_96	.503
383	yudixie_resnet18_object_class_0_240719	.502
384	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.500
385	alexnet_l2_3_robust	.500
386	convnext_base_fb_in22k_ft_in1k	.500
387	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.500
388	yolos_tiny	.499
389	mobilenet_v1_0.25_160	.499
390	mobilenet_v2_0.35_160	.497
391	yudixie_resnet18_distance_translation_rotation_0_240719	.497
392	compact_cornets_IT	.494
393	ReAlnet01_cornet_fov16	.493
394	resnet-50-pytorch	.491
395	resnet-50-robust	.491
396	r3m_resnet50	.491
397	vggface	.489
398	yudixie_resnet18_translation_rotation_0_240719	.489
399	vonealexnet	.489
400	yudixie_resnet18_distance_reg_0_240719	.488
401	yudixie_resnet18_distance_rotation_0_240719	.485
402	yudixie_resnet18_translation_reg_0_240719	.485
403	artResNet18_1	.484
404	ViT_L_32_imagenet1k	.483
405	resnet50_ijepacnn_linhead	.482
406	r3m_resnet50_nocrop	.479
407	compact_vgg19_IT	.479
408	convnext_base_fb_in1k	.477
409	convnext_base_fb_in1k_gram_aligned_dinov3	.477
410	mobilenet_v2_0.35_96	.476
411	mehrer2020_alexnet_training_seed_01_fov12	.476
412	yudixie_resnet18_rotation_reg_0_240719	.476
413	yudixie_resnet18_distance_translation_0_240719	.475
414	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.474
415	deit_small_imagenet_100_seed-0	.474
416	resnet50_supervised_linhead	.473
417	mobilenet_v1_0.25_128	.462
418	my-model	.462
419	mobilenet_v2_0.35_128	.457
420	resnet50_imagenet_10_seed-0	.457
421	mobilenet_v2_1-4_224_pytorch	.455
422	AlexNet_SIN_fov12	.447
423	prednet	.446
424	resnet18-depth_prediction	.443
425	alexnet_training_seed_01_fov4	.442
426	mehrer2020_alexnet_training_seed_01_fov16	.434
427	resnet50-cifar	.418
428	alexnet_linf_8_robust	.413
429	alexnet_fov12	.412
430	deepeisnn_ei_cifar10_vgg19	.405
431	deepeisnn_ei_cifar10_resnet18	.403
432	alexnet_robust_correct	.399
433	resnet18-contrastive_predictive	.394
434	yudixie_wbh_object_class_scaling_0415_run_2	.389
435	alexnet_fov16	.378
436	AlexNet_SIN_fov16	.374
437	gabor_filter_entropy_4x4_v2_forcedCosine	.371
438	gabor_filter_entropy_4x4_v2	.369
439	resnet18-autoencoder	.367
440	alexnet_training_seed_02	.366
441	briaai_rmbg_1_4	.364
442	v1-pyr-nodown	.362
443	resnet-152_v2_pytorch	.358
444	alexnet_training_seed_06	.356
445	yudixie_wbh_object_class_scaling_0415_run_0	.351
446	alexnet_training_seed_09	.350
447	CORnetZ_CIFAR10	.349
448	alexnet_training_seed_01	.347
449	yudixie_wbh_object_class_scaling_0415_run_1	.346
450	alexnet_training_seed_03	.345
451	alexnet_training_seed_07	.344
452	alexnet_training_seed_08	.343
453	alexnet_training_seed_10	.342
454	alexnet_training_seed_05	.341
455	resnet50_pretrained_with_retinal_waves	.340
456	CORnetZ_CIFAR10_bs32_20_04	.340
457	alexnet_training_seed_04	.336
458	yudixie_resnet50_random_0_240908	.331
459	mobilevit_small	.330
460	resnet-18_untrained	.329
461	resnet50_FractalDB	.328
462	resnet-50_untrained	.327
463	alexnet_training_seed_01_fov12	.322
464	resnet-50x2_untrained	.321
465	yudixie_wbh_object_class_scaling_0415_run_3	.320
466	gabor_filter_mean_abs_4x4_v2	.319
467	yudixie_resnet18_random_0_240719	.317
468	alexnet_training_seed_01_fov16	.304
469	resnet50_untrained_linhead	.303
470	resnet50_imagenet_1_seed-0	.298
471	resnet-18-LC_untrained	.270
472	vith14_untrained_linhead	.258
473	gabor_filter_entropy_4x4	.245
474	pr1_stl10_disentangled_alpha04	.215
475	predictive_coding_pc	.189
476	deit_small_imagenet_10_seed-0	.156
477	convnext_small_imagenet_10_seed-0	.121
478	fitvid_trained_on_physion	.117
479	deit_small_imagenet_1_seed-0	.102
480	convnext_small_imagenet_1_seed-0	.092
481	pixels	.075
482	my-model	.075
483	hmax	.033
484	pnasnet_large_halfPrecision
485	vith14_supervised_linhead
486	convnext_xxlarge:clip_laion2b_soup_ft_in1k
487	eva02_large_in22k
488	vit_huge_clip336_laion
489	persistence_mem

Benchmark bibtex

@misc{Sanghavi_DiCarlo_2021,
  title={Sanghavi2020},
  url={osf.io/chwdk},
  DOI={10.17605/OSF.IO/CHWDK},
  publisher={OSF},
  author={Sanghavi, Sachi and DiCarlo, James J},
  year={2021},
  month={Nov}
}

Ceiling

0.89.

Note that scores are relative to this ceiling.

Data: Sanghavi2020.V4

5760 stimuli recordings from 47 sites in V4

Metric: pls