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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	alexnet_fov4	.613
3	compact_resnet50_robust_V4	.601
4	custom_model_cv_18_dagger_408	.595
5	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.591
6	AdvProp_efficientnet-b4	.590
7	densenet-169-keras	.589
8	densenet-121-keras	.589
9	resnet50	.589
10	ReAlnet07_cornet	.588
11	ReAlnet08_cornet	.587
12	ReAlnet02_cornet	.587
13	compact_resnet50_V4	.586
14	ReAlnet10_cornet	.585
15	yudixie_resnet50_imagenet1kpret_0_240908	.584
16	resnet_50_v1	.584
17	resnet50-sup	.584
18	resnet_50_v1_spiking	.584
19	resnet_50_v1_spiking_l4	.584
20	resnet_50_v1_spiking_l4a	.584
21	resnet50_tutorial	.584
22	resnet_50_v1_spiking_l3	.584
23	yudixie_resnet50_imagenet1kpret_0_240312	.584
24	ReAlnet03_cornet	.584
25	ReAlnet05_cornet	.583
26	efficientnet_b1_imagenet_full	.583
27	ReAlnet04_cornet	.583
28	densenet-201-keras	.582
29	ReAlnet09_cornet	.582
30	antialiased-r50	.582
31	antialiased-rnext101_32x8d	.581
32	resnet50_random_linf8_perturb	.581
33	efficientnet_b2_imagenet_full	.581
34	SWSL_resnet50	.580
35	resnet34_ecoset_full	.580
36	focalnet_tiny_lrf_in1k	.580
37	ReAlnet06_cornet	.580
38	resnet50_random_l2_perturb	.580
39	resnet50-SIN_IN_IN	.579
40	resnet_SIN_IN_FT_IN	.579
41	resnet18-colorization	.579
42	ReAlnet01_cornet	.579
43	resnet-50_v1-tf	.578
44	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.578
45	inception_v1-tf	.577
46	resnet50-SIN_IN	.576
47	resnet-101_v1-tf	.576
48	resnet50_linf_4_robust	.576
49	AdvProp_efficientnet-b8	.575
50	effnetv2m_custom384	.575
51	xception-keras	.575
52	ReAlnet02_ALL	.575
53	resnext101_32x8d_wsl	.575
54	ReAlnet01_ALL	.575
55	ReAlnet08_ALL	.575
56	ReAlnet09_ALL	.574
57	resnet-152_v1-tf	.574
58	vgg_16	.574
59	vonegrcnn_62e_nobn	.574
60	ReAlnet07_ALL	.574
61	resnet-18-LC_w_sh_100_iter_conv_init_m	.574
62	ReAlnet06_ALL	.574
63	vgg-16-keras	.574
64	vit_base_patch16_clip_224:openai_ft_in1k	.574
65	vonegrcnn_52e_full	.574
66	resnext101_32x16d_wsl	.574
67	resnet152_imagenet_full	.574
68	vision_transformer_vit_large_patch16_224	.574
69	ReAlnet04_ALL	.574
70	deit_large_imagenet_full_seed-0	.574
71	ReAlnet03_ALL	.574
72	BiT-M-R101x3	.573
73	vonegrcnn_47e	.573
74	ReAlnet10_ALL	.573
75	resnet-50_v2-tf	.573
76	ReAlnet05_ALL	.573
77	resnet50_ewconplus_wzc	.573
78	resnet152_ecoset_full	.572
79	resnet-18-LC_d_w_sh_1x1_conv_init_m	.572
80	effnetb1_272x240	.572
81	AdvProp_efficientnet-b6	.572
82	resnet50_imagenet_100_seed-0	.572
83	BiT-S-R101x3	.571
84	omnivore_swinB	.571
85	Res2Net50_26w_4s	.571
86	resnet101_ecoset_full	.571
87	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.571
88	AT_efficientnet-b7	.570
89	resnet18_imagenet_full	.570
90	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.570
91	voneresnet-50	.570
92	resnet50_l2_3_robust	.570
93	0.5x_resnet-18_LC_w_sh_10_iter	.569
94	compact_vgg19_V4	.569
95	AdvProp_efficientnet-b7	.569
96	resnet18_imagenet21kP	.569
97	yudixie_resnet18_imagenet1kpret_0_240719	.569
98	inception_resnet_v2	.568
99	resnet18_ecoset_full	.568
100	konkle_alexnetgn_ipcl_ref01_primary_model	.568
101	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.568
102	inception_v2-tf	.568
103	voneresnet-50-robust	.568
104	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.568
105	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.567
106	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.567
107	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.567
108	AdvProp_efficientnet-b2	.567
109	mobilenet_v1_1.0_160	.567
110	convnext_tiny_imagenet_full_seed-0	.567
111	AdvProp_efficientnet-b0	.567
112	resnext101_32x48d_wsl	.567
113	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.567
114	efficientnet_b0_imagenet_full	.567
115	efficientnet_b0	.566
116	AT_efficientnet-b2	.566
117	mobilenet_v2_1_4_224	.566
118	resnet101_imagenet_full	.566
119	BiT-M-R152x2	.566
120	texture_shape_resnet50_trained_on_SIN	.566
121	resnet34_imagenet_full	.566
122	resnet-18-LC_w_sh_100_iter_m	.565
123	SWSL_resnext101_32x8d	.565
124	resnet-18-LC_w_sh_1_iter_m	.565
125	convnext_small_imagenet_full_seed-0	.565
126	omnivore_swinS	.565
127	resnet50_imagenet_full	.565
128	convnext_base_imagenet_full_seed-0	.565
129	resnet-152_v2-tf	.565
130	antialias-resnet152	.564
131	CORnet-S	.564
132	compact_resnet50_IT	.564
133	cv_18_dagger_408_pretrained	.564
134	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.564
135	BiT-S-R50x3	.563
136	omnivore_swinT	.563
137	resnet50_robust_l2_eps1	.563
138	BiT-M-R152x4	.563
139	resnet101	.563
140	vit_relpos_base_patch16_clsgap_224:sw_in1k	.563
141	resnet-101_v2-tf	.562
142	voneresnet-50-non_stochastic	.562
143	mobilenet_v1_1.0_224	.562
144	CLIP-RN50	.562
145	resnet-18	.562
146	resnet-18-LC_w_sh_1_iter_conv_init_m	.562
147	FrankRobWobv0	.562
148	resnet-18-LC_w_sh_10_iter_conv_init_m	.561
149	convnext_tiny_sup	.561
150	grcnn_v2_text_noise	.561
151	VOneCORnet-S	.561
152	resnet50_moco_v2	.561
153	mobilenet_v2_1.0_128-tf	.561
154	convnext_femto_ols:d1_in1k	.561
155	BiT-S-R152x2	.561
156	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.560
157	nasnet_mobile	.560
158	BiT-M-R101x1	.560
159	resnext101_32x32d_wsl	.560
160	mobilenet_v2_1_3_224	.559
161	AT_efficientnet-b4	.559
162	resnet50-vicreg	.559
163	densenet-169	.559
164	regnet_y_400mf	.559
165	AlexNet_SIN_fov4	.558
166	barlow-twins-resnet50	.558
167	inception_v3-tf	.558
168	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.558
169	deit_small_imagenet_full_seed-0	.557
170	nasnet_large-tf	.557
171	densenet-201	.557
172	grcnn_109	.557
173	resnet50_ecoset_full	.557
174	resnet50-vicregl0p9	.557
175	BiT-M-R50x1	.556
176	resnet-18_test_m	.556
177	resnet18-local_aggregation	.556
178	mobilenet_v2_1.3_224-tf	.556
179	cvt_cvt-21-384-in1k_4_LucyV4	.555
180	cvt_cvt-13-384-in1k_4_LucyV4	.554
181	resnet50-vicregl0p75	.554
182	resnet50-VITO-8deg-cc	.554
183	pnasnet_large-tf	.554
184	0.5x_resnet-18_LC_w_sh_100_iter	.554
185	grcnn	.554
186	resnet_50_v2	.554
187	tv_efficientnet-b1	.554
188	resnet50-barlow	.553
189	mobilenet_v2_1_0_128	.553
190	alexnet_random_linf8_perturb	.553
191	densenet-121	.553
192	vgg_19	.553
193	inception_v3	.553
194	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.553
195	mobilenet_v1_0.75_128	.553
196	mobilenet_v2_0_75_224	.553
197	RN50	.552
198	convnext_tiny:in12k_ft_in1k	.552
199	alexnet_random_l2_3_perturb	.552
200	deit_base_imagenet_full_seed-0	.552
201	vonealexnet_gaussian_noise_std4_fixed	.552
202	ViT-B/32	.552
203	CLIP_resnet50	.552
204	CLIP_resnet50_float32	.552
205	CLIP_ViT-B_32	.551
206	cornet_s	.551
207	mobilenet_v2_1.4_224-tf	.551
208	mobilenet_v2_1_0_192	.550
209	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.550
210	mobilenet_v2_1.0_160-tf	.550
211	fixres_resnext101_32x48d_wsl	.550
212	cvt_cvt-13-224-in1k_4_LucyV4	.550
213	mobilenet_v1_1.0_192	.550
214	compact_resnet50_robust_IT	.549
215	mobilenet_v2_0.75_224-tf	.549
216	mobilenet_v1_0.75_160	.549
217	mobilenet_v2_1_0_224	.549
218	resnet50-moclr8deg	.549
219	compact_cornets_V4	.549
220	mobilenet_v2_0_75_192	.549
221	grcnn_robust_v1	.549
222	convnext_large_imagenet_full_seed-0	.548
223	resnet18-instance_recognition	.548
224	BiT-S-R101x1	.548
225	BiT-S-R50x1	.548
226	alexnet	.548
227	alexnet_ks_torevert	.548
228	convnext_xlarge:fb_in22k_ft_in1k	.548
229	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.548
230	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.548
231	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.548
232	convnext_base:clip_laiona_augreg_ft_in1k_384	.547
233	vgg-19-keras	.547
234	BiT-M-R50x3	.547
235	resnet50-simclr-vissl	.546
236	mobilenet_v2_1.0_192-tf	.546
237	mobilenet_v1_1.0_128	.546
238	0.5x_resnet-18_LC_w_sh_1_iter	.546
239	imagenet_l2_3_0	.546
240	0.5x_resnet-18	.546
241	vit_large_patch14_clip_224:openai_ft_in1k	.545
242	mobilenet_v1_0.75_192	.545
243	resnet50-vitoimagevidnet8	.545
244	resnet50_robust_l2_eps3	.545
245	yudixie_resnet50_object_class_0_240908	.544
246	mobilenet_v1_0.75_224	.544
247	resnet50_byol	.544
248	resnet50_byol	.544
249	resnet50-SIN	.544
250	mobilenet_v2_0.75_192-tf	.544
251	cvt_cvt-21-224-in1k_4_LucyV4	.542
252	nasnet_mobile-tf	.542
253	vit_base_patch16_dinov3-lvd1689m	.541
254	efficientnet-b7	.541
255	mobilenet_v2_0.75_160-tf	.541
256	mobilenet_v2_1.0_224-tf	.541
257	inception_v4-tf	.541
258	mobilenet_v2_1_0_160	.541
259	mobilenet_v2_0.75_128	.540
260	squeezenet1_0	.540
261	BiT-S-R152x4	.540
262	yudixie_resnet50_translation_reg_0_240908	.540
263	vit_base_patch14_dinov2-lvd142m	.540
264	yudixie_resnet50_category_class_0_240908	.539
265	CORnet-Z	.539
266	resnet-18-LC_1st_conv_m	.538
267	mobilenet_v2_0_5_192	.538
268	ReAlnet01_cornet_fov12	.538
269	resnet18-relative_position	.537
270	resnet-18-LC_m	.537
271	vit_base_patch14_reg4_dinov2-lvd142m	.537
272	mobilenet_v1_0.5_192	.537
273	resnet-34	.537
274	vit_large_patch14_clip_224:laion2b_ft_in1k	.536
275	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.536
276	mobilenet_v2_0_5_224	.536
277	shufflenet_v2_x1_0	.536
278	squeezenet1_1	.535
279	RN50	.535
280	inception_v1	.535
281	resnet-18-LC_w_sh_10_iter_m	.535
282	resnet18-contrastive_multiview	.535
283	mobilenet_v2_0.5_224-tf	.534
284	mobilenet_v2_0.5_128	.534
285	yudixie_resnet50_distance_translation_0_240908	.534
286	mobilenet_v1_0.25_224	.533
287	mobilenet_v1_0.5_224	.533
288	convnext_small_imagenet_100_seed-0	.532
289	resnet50_linf_8_robust	.532
290	mobilenet_v2_0_75_160	.531
291	yudixie_resnet50_translation_rotation_0_240908	.531
292	yudixie_resnet50_distance_reg_0_240908	.531
293	resnet18-supervised	.531
294	yudixie_resnet50_distance_translation_rotation_0_240908	.531
295	yudixie_resnet50_distance_rotation_0_240908	.530
296	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.530
297	mobilenet_v2_1.0_96	.529
298	vit_large_patch14_clip_336:laion2b_ft_in1k	.528
299	mobilenet_v2_0.5_192-tf	.528
300	convnext_large:fb_in22k_ft_in1k	.528
301	mobilenet_v1_0.5_160	.528
302	0.5x_resnet-18_LC	.527
303	resnet-18-LC_conv_init_m	.527
304	mobilenet_v1_0.5_128	.524
305	mobilenet_v2_0.35_224	.523
306	alexnet_reduced_aliasing_early_checkpoint	.522
307	resnet18-deepcluster	.522
308	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.521
309	resnet50_primary_visual_cortex	.520
310	mobilenet_v2_0.5_160	.520
311	resnet50_simclr	.520
312	r3m_resnet18	.519
313	ReAlnet10	.519
314	r3m_resnet34	.517
315	mobilenet_v2_0.35_192	.517
316	ReAlnet02	.515
317	yudixie_resnet18_category_class_0_240719	.515
318	ReAlnet08	.515
319	alexnet_early_checkpoint	.515
320	mobilenet_v2_0.75_96	.514
321	ReAlnet07	.513
322	texture_shape_alexnet_trained_on_SIN	.512
323	ReAlnet03	.510
324	yudixie_resnet50_rotation_reg_0_240908	.510
325	AlexNet_SIN	.509
326	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.509
327	ReAlnet06	.509
328	imagenet_l2_10_0	.509
329	ReAlnet01	.508
330	ReAlnet09	.507
331	ReAlnet04	.506
332	mobilenet_v1_0.25_192	.506
333	ReAlnet05	.505
334	mobilenet_v2_0.5_96	.503
335	yudixie_resnet18_object_class_0_240719	.502
336	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.500
337	alexnet_l2_3_robust	.500
338	yolos_tiny	.499
339	mobilenet_v1_0.25_160	.499
340	mobilenet_v2_0.35_160	.497
341	yudixie_resnet18_distance_translation_rotation_0_240719	.497
342	compact_cornets_IT	.494
343	ReAlnet01_cornet_fov16	.493
344	resnet50	.493
345	resnet-50-pytorch	.491
346	resnet-50-robust	.491
347	r3m_resnet50	.491
348	vggface	.489
349	yudixie_resnet18_translation_rotation_0_240719	.489
350	yudixie_resnet18_distance_reg_0_240719	.488
351	yudixie_resnet18_distance_rotation_0_240719	.485
352	yudixie_resnet18_translation_reg_0_240719	.485
353	artResNet18_1	.484
354	ViT_L_32_imagenet1k	.483
355	r3m_resnet50_nocrop	.479
356	compact_vgg19_IT	.479
357	mobilenet_v2_0.35_96	.476
358	yudixie_resnet18_rotation_reg_0_240719	.476
359	yudixie_resnet18_distance_translation_0_240719	.475
360	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.474
361	deit_small_imagenet_100_seed-0	.474
362	mobilenet_v1_0.25_128	.462
363	my-model	.462
364	mobilenet_v2_0.35_128	.457
365	resnet50_imagenet_10_seed-0	.457
366	mobilenet_v2_1-4_224_pytorch	.455
367	AlexNet_SIN_fov12	.447
368	prednet	.446
369	resnet18-depth_prediction	.443
370	alexnet_training_seed_01_fov4	.442
371	resnet50-cifar	.418
372	alexnet_linf_8_robust	.413
373	alexnet_fov12	.412
374	aughost_fair_resnet18	.410
375	alexnet_robust_correct	.399
376	resnet18-contrastive_predictive	.394
377	alexnet_fov16	.378
378	AlexNet_SIN_fov16	.374
379	resnet18-autoencoder	.367
380	alexnet_training_seed_02	.366
381	briaai_rmbg_1_4	.364
382	v1-pyr-nodown	.362
383	resnet-152_v2_pytorch	.358
384	resnet50-meshes-lt-100-original-pretrained	.358
385	alexnet_training_seed_06	.356
386	alexnet_training_seed_09	.350
387	CORnetZ_CIFAR10	.349
388	alexnet_training_seed_01	.347
389	alexnet_training_seed_03	.345
390	resnet50-meshes-lt-100-original-scratch	.345
391	alexnet_training_seed_07	.344
392	alexnet_training_seed_08	.343
393	alexnet_training_seed_10	.342
394	alexnet_training_seed_05	.341
395	resnet50_pretrained_with_retinal_waves	.340
396	CORnetZ_CIFAR10_bs32_20_04	.340
397	alexnet_training_seed_04	.336
398	yudixie_resnet50_random_0_240908	.331
399	mobilevit_small	.330
400	resnet-18_untrained	.329
401	resnet50_FractalDB	.328
402	resnet-50_untrained	.327
403	alexnet_training_seed_01_fov12	.322
404	resnet-50x2_untrained	.321
405	yudixie_resnet18_random_0_240719	.317
406	alexnet_training_seed_01_fov16	.304
407	resnet50_imagenet_1_seed-0	.298
408	resnet-18-LC_untrained	.270
409	deit_small_imagenet_10_seed-0	.156
410	convnext_small_imagenet_10_seed-0	.121
411	fitvid_trained_on_physion	.117
412	deit_small_imagenet_1_seed-0	.102
413	convnext_small_imagenet_1_seed-0	.092
414	pixels	.075
415	my-model	.075
416	pnasnet_large_halfPrecision

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