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

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