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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	custom_model_cv_18_dagger_408	.669
2	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.664
3	AdvProp_efficientnet-b4	.663
4	densenet-169-keras	.663
5	densenet-121-keras	.662
6	resnet50	.662
7	ReAlnet07_cornet	.661
8	ReAlnet08_cornet	.661
9	ReAlnet02_cornet	.660
10	ReAlnet10_cornet	.658
11	yudixie_resnet50_imagenet1kpret_0_240908	.656
12	resnet_50_v1	.656
13	resnet50-sup	.656
14	resnet_50_v1_spiking	.656
15	resnet_50_v1_spiking_l4	.656
16	resnet_50_v1_spiking_l4a	.656
17	resnet50_tutorial	.656
18	resnet_50_v1_spiking_l3	.656
19	yudixie_resnet50_imagenet1kpret_0_240312	.656
20	ReAlnet03_cornet	.656
21	ReAlnet05_cornet	.656
22	efficientnet_b1_imagenet_full	.656
23	ReAlnet04_cornet	.655
24	densenet-201-keras	.655
25	ReAlnet09_cornet	.655
26	antialiased-r50	.655
27	antialiased-rnext101_32x8d	.654
28	resnet50_random_linf8_perturb	.653
29	efficientnet_b2_imagenet_full	.653
30	SWSL_resnet50	.653
31	resnet34_ecoset_full	.653
32	focalnet_tiny_lrf_in1k	.653
33	ReAlnet06_cornet	.652
34	resnet50_random_l2_perturb	.652
35	resnet50-SIN_IN_IN	.651
36	resnet_SIN_IN_FT_IN	.651
37	resnet18-colorization	.651
38	ReAlnet01_cornet	.651
39	resnet-50_v1-tf	.650
40	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.650
41	inception_v1-tf	.649
42	resnet50-SIN_IN	.648
43	resnet-101_v1-tf	.648
44	resnet50_linf_4_robust	.648
45	AdvProp_efficientnet-b8	.647
46	effnetv2m_custom384	.647
47	xception-keras	.647
48	ReAlnet02_ALL	.647
49	resnext101_32x8d_wsl	.646
50	ReAlnet01_ALL	.646
51	ReAlnet08_ALL	.646
52	ReAlnet09_ALL	.646
53	resnet-152_v1-tf	.646
54	vgg_16	.646
55	vonegrcnn_62e_nobn	.646
56	ReAlnet07_ALL	.646
57	resnet-18-LC_w_sh_100_iter_conv_init_m	.646
58	ReAlnet06_ALL	.646
59	vgg-16-keras	.646
60	vit_base_patch16_clip_224:openai_ft_in1k	.646
61	vonegrcnn_52e_full	.645
62	resnext101_32x16d_wsl	.645
63	resnet152_imagenet_full	.645
64	vision_transformer_vit_large_patch16_224	.645
65	ReAlnet04_ALL	.645
66	deit_large_imagenet_full_seed-0	.645
67	ReAlnet03_ALL	.645
68	BiT-M-R101x3	.645
69	vonegrcnn_47e	.645
70	ReAlnet10_ALL	.644
71	resnet-50_v2-tf	.644
72	ReAlnet05_ALL	.644
73	resnet152_ecoset_full	.644
74	resnet-18-LC_d_w_sh_1x1_conv_init_m	.643
75	effnetb1_272x240	.643
76	AdvProp_efficientnet-b6	.643
77	resnet50_imagenet_100_seed-0	.643
78	BiT-S-R101x3	.643
79	omnivore_swinB	.642
80	Res2Net50_26w_4s	.642
81	resnet101_ecoset_full	.642
82	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.642
83	AT_efficientnet-b7	.642
84	resnet18_imagenet_full	.641
85	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.641
86	voneresnet-50	.641
87	resnet50_l2_3_robust	.641
88	0.5x_resnet-18_LC_w_sh_10_iter	.640
89	AdvProp_efficientnet-b7	.640
90	resnet18_imagenet21kP	.640
91	yudixie_resnet18_imagenet1kpret_0_240719	.640
92	inception_resnet_v2	.639
93	resnet18_ecoset_full	.639
94	konkle_alexnetgn_ipcl_ref01_primary_model	.639
95	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.639
96	inception_v2-tf	.639
97	voneresnet-50-robust	.638
98	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.638
99	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.638
100	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.638
101	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.638
102	AdvProp_efficientnet-b2	.638
103	mobilenet_v1_1.0_160	.638
104	convnext_tiny_imagenet_full_seed-0	.638
105	AdvProp_efficientnet-b0	.638
106	resnext101_32x48d_wsl	.637
107	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.637
108	efficientnet_b0_imagenet_full	.637
109	efficientnet_b0	.636
110	AT_efficientnet-b2	.636
111	mobilenet_v2_1_4_224	.636
112	resnet101_imagenet_full	.636
113	BiT-M-R152x2	.636
114	texture_shape_resnet50_trained_on_SIN	.636
115	resnet34_imagenet_full	.636
116	resnet-18-LC_w_sh_100_iter_m	.636
117	SWSL_resnext101_32x8d	.636
118	resnet-18-LC_w_sh_1_iter_m	.636
119	convnext_small_imagenet_full_seed-0	.636
120	omnivore_swinS	.635
121	resnet50_imagenet_full	.635
122	convnext_base_imagenet_full_seed-0	.635
123	resnet-152_v2-tf	.635
124	antialias-resnet152	.634
125	CORnet-S	.634
126	cv_18_dagger_408_pretrained	.634
127	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.634
128	BiT-S-R50x3	.634
129	omnivore_swinT	.634
130	resnet50_robust_l2_eps1	.633
131	BiT-M-R152x4	.633
132	resnet101	.633
133	vit_relpos_base_patch16_clsgap_224:sw_in1k	.633
134	resnet-101_v2-tf	.632
135	voneresnet-50-non_stochastic	.632
136	mobilenet_v1_1.0_224	.632
137	CLIP-RN50	.632
138	resnet-18	.632
139	resnet-18-LC_w_sh_1_iter_conv_init_m	.632
140	FrankRobWobv0	.632
141	resnet-18-LC_w_sh_10_iter_conv_init_m	.631
142	convnext_tiny_sup	.631
143	grcnn_v2_text_noise	.631
144	VOneCORnet-S	.631
145	resnet50_moco_v2	.631
146	mobilenet_v2_1.0_128-tf	.631
147	convnext_femto_ols:d1_in1k	.631
148	BiT-S-R152x2	.631
149	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.630
150	nasnet_mobile	.630
151	BiT-M-R101x1	.630
152	resnext101_32x32d_wsl	.629
153	mobilenet_v2_1_3_224	.629
154	AT_efficientnet-b4	.629
155	resnet50-vicreg	.629
156	alexnet	.629
157	densenet-169	.629
158	regnet_y_400mf	.628
159	barlow-twins-resnet50	.627
160	inception_v3-tf	.627
161	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.627
162	deit_small_imagenet_full_seed-0	.627
163	nasnet_large-tf	.627
164	densenet-201	.627
165	grcnn_109	.626
166	resnet50_ecoset_full	.626
167	resnet50-vicregl0p9	.626
168	BiT-M-R50x1	.626
169	resnet-18_test_m	.625
170	resnet18-local_aggregation	.625
171	mobilenet_v2_1.3_224-tf	.625
172	cvt_cvt-21-384-in1k_4_LucyV4	.625
173	cvt_cvt-13-384-in1k_4_LucyV4	.623
174	resnet50-vicregl0p75	.623
175	resnet50-VITO-8deg-cc	.623
176	pnasnet_large-tf	.623
177	0.5x_resnet-18_LC_w_sh_100_iter	.623
178	grcnn	.623
179	resnet_50_v2	.623
180	tv_efficientnet-b1	.623
181	resnet50-barlow	.622
182	mobilenet_v2_1_0_128	.622
183	alexnet_random_linf8_perturb	.622
184	densenet-121	.622
185	vgg_19	.622
186	inception_v3	.622
187	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.622
188	mobilenet_v1_0.75_128	.621
189	mobilenet_v2_0_75_224	.621
190	RN50	.621
191	convnext_tiny:in12k_ft_in1k	.621
192	alexnet_random_l2_3_perturb	.621
193	deit_base_imagenet_full_seed-0	.621
194	vonealexnet_gaussian_noise_std4_fixed	.621
195	ViT-B/32	.621
196	CLIP_resnet50	.620
197	CLIP_resnet50_float32	.620
198	CLIP_ViT-B_32	.620
199	cornet_s	.619
200	mobilenet_v2_1.4_224-tf	.619
201	mobilenet_v2_1_0_192	.619
202	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.619
203	mobilenet_v2_1.0_160-tf	.619
204	fixres_resnext101_32x48d_wsl	.619
205	cvt_cvt-13-224-in1k_4_LucyV4	.618
206	mobilenet_v1_1.0_192	.618
207	mobilenet_v2_0.75_224-tf	.618
208	mobilenet_v1_0.75_160	.618
209	mobilenet_v2_1_0_224	.618
210	resnet50-moclr8deg	.618
211	mobilenet_v2_0_75_192	.617
212	grcnn_robust_v1	.617
213	convnext_large_imagenet_full_seed-0	.617
214	resnet18-instance_recognition	.617
215	BiT-S-R101x1	.617
216	BiT-S-R50x1	.617
217	alexnet	.617
218	alexnet-baseline	.617
219	alexnet	.617
220	alexnet	.617
221	alexnet	.617
222	alexnet	.617
223	alexnet	.617
224	alexnet	.617
225	alexnet	.617
226	alexnet_ks_torevert	.617
227	convnext_xlarge:fb_in22k_ft_in1k	.617
228	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.616
229	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.616
230	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.616
231	convnext_base:clip_laiona_augreg_ft_in1k_384	.615
232	vgg-19-keras	.615
233	BiT-M-R50x3	.615
234	resnet50-simclr-vissl	.614
235	mobilenet_v2_1.0_192-tf	.614
236	mobilenet_v1_1.0_128	.614
237	0.5x_resnet-18_LC_w_sh_1_iter	.614
238	imagenet_l2_3_0	.614
239	0.5x_resnet-18	.614
240	vit_large_patch14_clip_224:openai_ft_in1k	.613
241	mobilenet_v1_0.75_192	.613
242	resnet50-vitoimagevidnet8	.613
243	resnet50_robust_l2_eps3	.612
244	yudixie_resnet50_object_class_0_240908	.612
245	mobilenet_v1_0.75_224	.612
246	resnet50_byol	.612
247	resnet50_byol	.612
248	resnet50-SIN	.612
249	mobilenet_v2_0.75_192-tf	.611
250	cvt_cvt-21-224-in1k_4_LucyV4	.609
251	nasnet_mobile-tf	.609
252	efficientnet-b7	.609
253	mobilenet_v2_0.75_160-tf	.609
254	mobilenet_v2_1.0_224-tf	.609
255	inception_v4-tf	.608
256	mobilenet_v2_1_0_160	.608
257	mobilenet_v2_0.75_128	.608
258	squeezenet1_0	.608
259	BiT-S-R152x4	.608
260	yudixie_resnet50_translation_reg_0_240908	.607
261	yudixie_resnet50_category_class_0_240908	.606
262	CORnet-Z	.606
263	resnet-18-LC_1st_conv_m	.605
264	mobilenet_v2_0_5_192	.605
265	resnet18-relative_position	.604
266	resnet-18-LC_m	.604
267	mobilenet_v1_0.5_192	.604
268	resnet-34	.604
269	vit_large_patch14_clip_224:laion2b_ft_in1k	.603
270	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.603
271	mobilenet_v2_0_5_224	.603
272	shufflenet_v2_x1_0	.602
273	squeezenet1_1	.602
274	RN50	.602
275	inception_v1	.602
276	resnet-18-LC_w_sh_10_iter_m	.602
277	resnet18-contrastive_multiview	.601
278	mobilenet_v2_0.5_224-tf	.601
279	mobilenet_v2_0.5_128	.601
280	yudixie_resnet50_distance_translation_0_240908	.600
281	mobilenet_v1_0.25_224	.600
282	mobilenet_v1_0.5_224	.599
283	convnext_small_imagenet_100_seed-0	.599
284	resnet50_linf_8_robust	.598
285	mobilenet_v2_0_75_160	.598
286	yudixie_resnet50_translation_rotation_0_240908	.597
287	yudixie_resnet50_distance_reg_0_240908	.597
288	resnet18-supervised	.597
289	yudixie_resnet50_distance_translation_rotation_0_240908	.597
290	yudixie_resnet50_distance_rotation_0_240908	.596
291	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.596
292	mobilenet_v2_1.0_96	.595
293	vit_large_patch14_clip_336:laion2b_ft_in1k	.594
294	mobilenet_v2_0.5_192-tf	.594
295	convnext_large:fb_in22k_ft_in1k	.594
296	mobilenet_v1_0.5_160	.593
297	0.5x_resnet-18_LC	.593
298	resnet-18-LC_conv_init_m	.592
299	mobilenet_v1_0.5_128	.589
300	mobilenet_v2_0.35_224	.588
301	alexnet_reduced_aliasing_early_checkpoint	.588
302	resnet18-deepcluster	.587
303	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.585
304	resnet50_primary_visual_cortex	.585
305	mobilenet_v2_0.5_160	.585
306	resnet50_simclr	.585
307	r3m_resnet18	.584
308	ReAlnet10	.583
309	r3m_resnet34	.581
310	mobilenet_v2_0.35_192	.581
311	ReAlnet02	.579
312	yudixie_resnet18_category_class_0_240719	.579
313	ReAlnet08	.579
314	alexnet_early_checkpoint	.579
315	mobilenet_v2_0.75_96	.578
316	ReAlnet07	.577
317	texture_shape_alexnet_trained_on_SIN	.575
318	ReAlnet03	.574
319	yudixie_resnet50_rotation_reg_0_240908	.573
320	AlexNet_SIN	.573
321	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.573
322	ReAlnet06	.573
323	imagenet_l2_10_0	.572
324	ReAlnet01	.572
325	ReAlnet09	.570
326	ReAlnet04	.569
327	mobilenet_v1_0.25_192	.569
328	ReAlnet05	.568
329	mobilenet_v2_0.5_96	.566
330	yudixie_resnet18_object_class_0_240719	.565
331	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.562
332	alexnet_l2_3_robust	.562
333	yolos_tiny	.561
334	mobilenet_v1_0.25_160	.561
335	mobilenet_v2_0.35_160	.559
336	yudixie_resnet18_distance_translation_rotation_0_240719	.559
337	resnet50	.554
338	resnet-50-pytorch	.552
339	resnet-50-robust	.552
340	r3m_resnet50	.552
341	vggface	.550
342	yudixie_resnet18_translation_rotation_0_240719	.549
343	yudixie_resnet18_distance_reg_0_240719	.548
344	yudixie_resnet18_distance_rotation_0_240719	.545
345	yudixie_resnet18_translation_reg_0_240719	.545
346	artResNet18_1	.544
347	ViT_L_32_imagenet1k	.543
348	r3m_resnet50_nocrop	.539
349	mobilenet_v2_0.35_96	.536
350	yudixie_resnet18_rotation_reg_0_240719	.535
351	yudixie_resnet18_distance_translation_0_240719	.534
352	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.534
353	deit_small_imagenet_100_seed-0	.533
354	mobilenet_v1_0.25_128	.520
355	my-model	.519
356	mobilenet_v2_0.35_128	.514
357	resnet50_imagenet_10_seed-0	.514
358	mobilenet_v2_1-4_224_pytorch	.512
359	prednet	.502
360	resnet18-depth_prediction	.498
361	resnet50-cifar	.471
362	alexnet_linf_8_robust	.464
363	alexnet_robust_correct	.448
364	resnet18-contrastive_predictive	.443
365	resnet18-autoencoder	.412
366	alexnet_training_seed_02	.411
367	briaai_rmbg_1_4	.409
368	v1-pyr-nodown	.407
369	resnet-152_v2_pytorch	.403
370	resnet50-meshes-lt-100-original-pretrained	.403
371	alexnet_training_seed_06	.400
372	alexnet_training_seed_09	.394
373	CORnetZ_CIFAR10	.392
374	alexnet_training_seed_01	.390
375	alexnet_training_seed_03	.388
376	resnet50-meshes-lt-100-original-scratch	.388
377	alexnet_training_seed_07	.387
378	alexnet_training_seed_08	.386
379	alexnet_training_seed_10	.385
380	alexnet_training_seed_05	.384
381	resnet50_pretrained_with_retinal_waves	.382
382	CORnetZ_CIFAR10_bs32_20_04	.382
383	alexnet_training_seed_04	.378
384	yudixie_resnet50_random_0_240908	.372
385	mobilevit_small	.371
386	resnet-18_untrained	.369
387	resnet50_FractalDB	.369
388	resnet-50_untrained	.368
389	resnet-50x2_untrained	.361
390	yudixie_resnet18_random_0_240719	.356
391	resnet50_imagenet_1_seed-0	.335
392	resnet-18-LC_untrained	.303
393	deit_small_imagenet_10_seed-0	.175
394	convnext_small_imagenet_10_seed-0	.136
395	fitvid_trained_on_physion	.132
396	deit_small_imagenet_1_seed-0	.114
397	convnext_small_imagenet_1_seed-0	.104
398	pixels	.085
399	my-model	.085
400	resnet18-simclr
401	openclip
402	resnet50_ImageNet
403	resnet_152_v1
404	ConvLSTM
405	PredRNN
406	SimVP
407	TAU
408	MIM
409	hmax
410	densenet_201_pytorch
411	pnasnet_large_pytorch
412	inception_v3_pytorch
413	inception_v4
414	xception
415	blt_vs
416	pnasnet_large
417	nasnet_large
418	resnet_101_v2
419	convnext_xxlarge:clip_laion2b_soup_ft_in1k
420	vonegrcnn_62e_nobn
421	resnet_152_v2
422	resnet_101_v1
423	vonegrcnn_47e
424	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k
425	vonegrcnn_52e_full
426	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k

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