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

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