Leaderboard Explore Compare Profile Community Blog FAQ Competition 2024 Report Issue

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	resnet50_ewconplus_wzc_seed4_2_323	.586
14	resnet50_ewconplus_wzc_seed3_2_323	.586
15	compact_resnet50_V4	.586
16	resnet50_ewconplus_wzc_seed2_2__323	.585
17	ReAlnet10_cornet	.585
18	yudixie_resnet50_imagenet1kpret_0_240908	.584
19	resnet_50_v1	.584
20	resnet50-sup	.584
21	resnet_50_v1_spiking	.584
22	resnet_50_v1_spiking_l4	.584
23	resnet_50_v1_spiking_l4a	.584
24	resnet50_tutorial	.584
25	resnet_50_v1_spiking_l3	.584
26	yudixie_resnet50_imagenet1kpret_0_240312	.584
27	ReAlnet03_cornet	.584
28	ReAlnet05_cornet	.583
29	efficientnet_b1_imagenet_full	.583
30	ReAlnet04_cornet	.583
31	densenet-201-keras	.582
32	ReAlnet09_cornet	.582
33	antialiased-r50	.582
34	antialiased-rnext101_32x8d	.581
35	resnet50_ewconplus_wzc_seed6_2_323	.581
36	resnet50_ewconplus_wzc_seed5_2__323	.581
37	resnet50_random_linf8_perturb	.581
38	efficientnet_b2_imagenet_full	.581
39	SWSL_resnet50	.580
40	resnet34_ecoset_full	.580
41	focalnet_tiny_lrf_in1k	.580
42	ReAlnet06_cornet	.580
43	resnet50_random_l2_perturb	.580
44	resnet50-SIN_IN_IN	.579
45	resnet_SIN_IN_FT_IN	.579
46	resnet50_ewconplus_noseed_2_323	.579
47	resnet18-colorization	.579
48	ReAlnet01_cornet	.579
49	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.578
50	deit3_base_patch16_224_fb_in1k	.578
51	resnet-50_v1-tf	.578
52	resnet50_ewconplus_wzc_2_323	.578
53	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.578
54	inception_v1-tf	.577
55	resnet50_ewconplus_wzc_seed7_2_323	.577
56	deit3_base_patch16_224_fb_in22k_ft_in1k	.576
57	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.576
58	resnet50-SIN_IN	.576
59	resnet-101_v1-tf	.576
60	resnet50_linf_4_robust	.576
61	AdvProp_efficientnet-b8	.575
62	effnetv2m_custom384	.575
63	xception-keras	.575
64	ReAlnet02_ALL	.575
65	resnext101_32x8d_wsl	.575
66	ReAlnet01_ALL	.575
67	ReAlnet08_ALL	.575
68	ReAlnet09_ALL	.574
69	resnet-152_v1-tf	.574
70	vgg_16	.574
71	vonegrcnn_62e_nobn	.574
72	ReAlnet07_ALL	.574
73	resnet-18-LC_w_sh_100_iter_conv_init_m	.574
74	ReAlnet06_ALL	.574
75	vgg-16-keras	.574
76	vit_base_patch16_clip_224:openai_ft_in1k	.574
77	vonegrcnn_52e_full	.574
78	resnext101_32x16d_wsl	.574
79	resnet152_imagenet_full	.574
80	vision_transformer_vit_large_patch16_224	.574
81	ReAlnet04_ALL	.574
82	deit_large_imagenet_full_seed-0	.574
83	ReAlnet03_ALL	.574
84	BiT-M-R101x3	.573
85	vonegrcnn_47e	.573
86	ReAlnet10_ALL	.573
87	resnet-50_v2-tf	.573
88	ReAlnet05_ALL	.573
89	resnet50_ewconplus_wzc	.573
90	resnet50_st_wzc_seed4_2_323	.572
91	resnet152_ecoset_full	.572
92	resnet-18-LC_d_w_sh_1x1_conv_init_m	.572
93	effnetb1_272x240	.572
94	AdvProp_efficientnet-b6	.572
95	resnet50_imagenet_100_seed-0	.572
96	BiT-S-R101x3	.571
97	omnivore_swinB	.571
98	Res2Net50_26w_4s	.571
99	resnet101_ecoset_full	.571
100	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.571
101	AT_efficientnet-b7	.570
102	resnet18_imagenet_full	.570
103	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.570
104	voneresnet-50	.570
105	resnet50_l2_3_robust	.570
106	0.5x_resnet-18_LC_w_sh_10_iter	.569
107	compact_vgg19_V4	.569
108	AdvProp_efficientnet-b7	.569
109	resnet18_imagenet21kP	.569
110	yudixie_resnet18_imagenet1kpret_0_240719	.569
111	yudixie_wbh_object_class_scaling_0415_imagenet	.569
112	inception_resnet_v2	.568
113	resnet18_ecoset_full	.568
114	konkle_alexnetgn_ipcl_ref01_primary_model	.568
115	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.568
116	inception_v2-tf	.568
117	voneresnet-50-robust	.568
118	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.568
119	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.567
120	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.567
121	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.567
122	AdvProp_efficientnet-b2	.567
123	mobilenet_v1_1.0_160	.567
124	convnext_tiny_imagenet_full_seed-0	.567
125	AdvProp_efficientnet-b0	.567
126	resnext101_32x48d_wsl	.567
127	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.567
128	efficientnet_b0_imagenet_full	.567
129	efficientnet_b0	.566
130	AT_efficientnet-b2	.566
131	mobilenet_v2_1_4_224	.566
132	resnet101_imagenet_full	.566
133	BiT-M-R152x2	.566
134	texture_shape_resnet50_trained_on_SIN	.566
135	resnet34_imagenet_full	.566
136	resnet-18-LC_w_sh_100_iter_m	.565
137	SWSL_resnext101_32x8d	.565
138	resnet-18-LC_w_sh_1_iter_m	.565
139	convnext_small_imagenet_full_seed-0	.565
140	omnivore_swinS	.565
141	resnet50_imagenet_full	.565
142	resnet50_st_wzc_noseed_2_323	.565
143	convnext_base_imagenet_full_seed-0	.565
144	resnet-152_v2-tf	.565
145	antialias-resnet152	.564
146	CORnet-S	.564
147	compact_resnet50_IT	.564
148	cv_18_dagger_408_pretrained	.564
149	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.564
150	BiT-S-R50x3	.563
151	omnivore_swinT	.563
152	resnet50_st_wzc_seed5_2_323	.563
153	resnet50_robust_l2_eps1	.563
154	BiT-M-R152x4	.563
155	resnet101	.563
156	resnet50_st_wzc_seed6_2_323	.563
157	vit_relpos_base_patch16_clsgap_224:sw_in1k	.563
158	resnet-101_v2-tf	.562
159	voneresnet-50-non_stochastic	.562
160	mobilenet_v1_1.0_224	.562
161	CLIP-RN50	.562
162	resnet-18	.562
163	resnet-18-LC_w_sh_1_iter_conv_init_m	.562
164	FrankRobWobv0	.562
165	resnet-18-LC_w_sh_10_iter_conv_init_m	.561
166	convnext_tiny_sup	.561
167	grcnn_v2_text_noise	.561
168	VOneCORnet-S	.561
169	resnet50_moco_v2	.561
170	mobilenet_v2_1.0_128-tf	.561
171	convnext_femto_ols:d1_in1k	.561
172	BiT-S-R152x2	.561
173	resnet50_st_wzc_seed7_2_323	.561
174	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.560
175	nasnet_mobile	.560
176	BiT-M-R101x1	.560
177	resnext101_32x32d_wsl	.560
178	mobilenet_v2_1_3_224	.559
179	AT_efficientnet-b4	.559
180	resnet50-vicreg	.559
181	densenet-169	.559
182	regnet_y_400mf	.559
183	resnet50_st_wzc_2_323	.558
184	AlexNet_SIN_fov4	.558
185	barlow-twins-resnet50	.558
186	inception_v3-tf	.558
187	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.558
188	resnet50_st_wzc_2	.558
189	deit_small_imagenet_full_seed-0	.557
190	nasnet_large-tf	.557
191	densenet-201	.557
192	grcnn_109	.557
193	resnet50_ecoset_full	.557
194	resnet50_st_wzc_seed3_2_323	.557
195	resnet50-vicregl0p9	.557
196	BiT-M-R50x1	.556
197	resnet-18_test_m	.556
198	resnet18-local_aggregation	.556
199	mobilenet_v2_1.3_224-tf	.556
200	cvt_cvt-21-384-in1k_4_LucyV4	.555
201	cvt_cvt-13-384-in1k_4_LucyV4	.554
202	resnet50-vicregl0p75	.554
203	resnet50-VITO-8deg-cc	.554
204	pnasnet_large-tf	.554
205	0.5x_resnet-18_LC_w_sh_100_iter	.554
206	grcnn	.554
207	resnet_50_v2	.554
208	tv_efficientnet-b1	.554
209	resnet50-barlow	.553
210	mobilenet_v2_1_0_128	.553
211	alexnet_random_linf8_perturb	.553
212	densenet-121	.553
213	vgg_19	.553
214	inception_v3	.553
215	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.553
216	mobilenet_v1_0.75_128	.553
217	mobilenet_v2_0_75_224	.553
218	RN50	.552
219	convnext_tiny:in12k_ft_in1k	.552
220	alexnet_random_l2_3_perturb	.552
221	deit_base_imagenet_full_seed-0	.552
222	vonealexnet_gaussian_noise_std4_fixed	.552
223	ViT-B/32	.552
224	CLIP_resnet50	.552
225	CLIP_resnet50_float32	.552
226	CLIP_ViT-B_32	.551
227	cornet_s	.551
228	mobilenet_v2_1.4_224-tf	.551
229	mobilenet_v2_1_0_192	.550
230	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.550
231	mobilenet_v2_1.0_160-tf	.550
232	fixres_resnext101_32x48d_wsl	.550
233	cvt_cvt-13-224-in1k_4_LucyV4	.550
234	mobilenet_v1_1.0_192	.550
235	compact_resnet50_robust_IT	.549
236	mobilenet_v2_0.75_224-tf	.549
237	mobilenet_v1_0.75_160	.549
238	mobilenet_v2_1_0_224	.549
239	resnet50-moclr8deg	.549
240	compact_cornets_V4	.549
241	mobilenet_v2_0_75_192	.549
242	grcnn_robust_v1	.549
243	convnext_large_imagenet_full_seed-0	.548
244	resnet18-instance_recognition	.548
245	BiT-S-R101x1	.548
246	BiT-S-R50x1	.548
247	alexnet	.548
248	alexnet_ks_torevert	.548
249	convnext_xlarge:fb_in22k_ft_in1k	.548
250	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.548
251	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.548
252	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.548
253	convnext_base:clip_laiona_augreg_ft_in1k_384	.547
254	vgg-19-keras	.547
255	BiT-M-R50x3	.547
256	resnet50-simclr-vissl	.546
257	mobilenet_v2_1.0_192-tf	.546
258	mobilenet_v1_1.0_128	.546
259	0.5x_resnet-18_LC_w_sh_1_iter	.546
260	imagenet_l2_3_0	.546
261	0.5x_resnet-18	.546
262	vit_large_patch14_clip_224:openai_ft_in1k	.545
263	mobilenet_v1_0.75_192	.545
264	resnet50-vitoimagevidnet8	.545
265	resnet50_robust_l2_eps3	.545
266	yudixie_resnet50_object_class_0_240908	.544
267	mobilenet_v1_0.75_224	.544
268	resnet50_byol	.544
269	resnet50_byol	.544
270	resnet50-SIN	.544
271	mobilenet_v2_0.75_192-tf	.544
272	cvt_cvt-21-224-in1k_4_LucyV4	.542
273	nasnet_mobile-tf	.542
274	vit_base_patch16_dinov3-lvd1689m	.541
275	efficientnet-b7	.541
276	mobilenet_v2_0.75_160-tf	.541
277	mobilenet_v2_1.0_224-tf	.541
278	inception_v4-tf	.541
279	mobilenet_v2_1_0_160	.541
280	mobilenet_v2_0.75_128	.540
281	squeezenet1_0	.540
282	BiT-S-R152x4	.540
283	yudixie_resnet50_translation_reg_0_240908	.540
284	vit_base_patch14_dinov2-lvd142m	.540
285	yudixie_resnet50_category_class_0_240908	.539
286	CORnet-Z	.539
287	resnet-18-LC_1st_conv_m	.538
288	mobilenet_v2_0_5_192	.538
289	ReAlnet01_cornet_fov12	.538
290	resnet18-relative_position	.537
291	resnet-18-LC_m	.537
292	vit_base_patch14_reg4_dinov2-lvd142m	.537
293	mobilenet_v1_0.5_192	.537
294	resnet-34	.537
295	vit_large_patch14_clip_224:laion2b_ft_in1k	.536
296	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.536
297	mobilenet_v2_0_5_224	.536
298	shufflenet_v2_x1_0	.536
299	squeezenet1_1	.535
300	RN50	.535
301	inception_v1	.535
302	resnet-18-LC_w_sh_10_iter_m	.535
303	resnet18-contrastive_multiview	.535
304	mobilenet_v2_0.5_224-tf	.534
305	mobilenet_v2_0.5_128	.534
306	yudixie_resnet50_distance_translation_0_240908	.534
307	mobilenet_v1_0.25_224	.533
308	mobilenet_v1_0.5_224	.533
309	convnext_small_imagenet_100_seed-0	.532
310	resnet50_linf_8_robust	.532
311	mobilenet_v2_0_75_160	.531
312	yudixie_resnet50_translation_rotation_0_240908	.531
313	yudixie_resnet50_distance_reg_0_240908	.531
314	resnet18-supervised	.531
315	yudixie_resnet50_distance_translation_rotation_0_240908	.531
316	yudixie_resnet50_distance_rotation_0_240908	.530
317	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.530
318	resnet18_fair	.530
319	mobilenet_v2_1.0_96	.529
320	vit_large_patch14_clip_336:laion2b_ft_in1k	.528
321	mobilenet_v2_0.5_192-tf	.528
322	convnext_large:fb_in22k_ft_in1k	.528
323	mobilenet_v1_0.5_160	.528
324	0.5x_resnet-18_LC	.527
325	resnet-18-LC_conv_init_m	.527
326	mobilenet_v1_0.5_128	.524
327	mobilenet_v2_0.35_224	.523
328	alexnet_reduced_aliasing_early_checkpoint	.522
329	resnet18-deepcluster	.522
330	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.521
331	resnet50_primary_visual_cortex	.520
332	mobilenet_v2_0.5_160	.520
333	resnet50_simclr	.520
334	r3m_resnet18	.519
335	ReAlnet10	.519
336	r3m_resnet34	.517
337	mobilenet_v2_0.35_192	.517
338	ReAlnet02	.515
339	yudixie_resnet18_category_class_0_240719	.515
340	ReAlnet08	.515
341	alexnet_early_checkpoint	.515
342	mobilenet_v2_0.75_96	.514
343	ReAlnet07	.513
344	texture_shape_alexnet_trained_on_SIN	.512
345	ReAlnet03	.510
346	yudixie_resnet50_rotation_reg_0_240908	.510
347	AlexNet_SIN	.509
348	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.509
349	ReAlnet06	.509
350	imagenet_l2_10_0	.509
351	ReAlnet01	.508
352	deepeisnn_ei_imagenet_resnet18	.508
353	ReAlnet09	.507
354	ReAlnet04	.506
355	mobilenet_v1_0.25_192	.506
356	ReAlnet05	.505
357	mobilenet_v2_0.5_96	.503
358	yudixie_resnet18_object_class_0_240719	.502
359	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.500
360	alexnet_l2_3_robust	.500
361	convnext_base_fb_in22k_ft_in1k	.500
362	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.500
363	yolos_tiny	.499
364	mobilenet_v1_0.25_160	.499
365	mobilenet_v2_0.35_160	.497
366	yudixie_resnet18_distance_translation_rotation_0_240719	.497
367	compact_cornets_IT	.494
368	ReAlnet01_cornet_fov16	.493
369	resnet50	.493
370	resnet-50-pytorch	.491
371	resnet-50-robust	.491
372	r3m_resnet50	.491
373	vggface	.489
374	yudixie_resnet18_translation_rotation_0_240719	.489
375	yudixie_resnet18_distance_reg_0_240719	.488
376	yudixie_resnet18_distance_rotation_0_240719	.485
377	yudixie_resnet18_translation_reg_0_240719	.485
378	artResNet18_1	.484
379	ViT_L_32_imagenet1k	.483
380	r3m_resnet50_nocrop	.479
381	compact_vgg19_IT	.479
382	convnext_base_fb_in1k	.477
383	convnext_base_fb_in1k_gram_aligned_dinov3	.477
384	mobilenet_v2_0.35_96	.476
385	yudixie_resnet18_rotation_reg_0_240719	.476
386	yudixie_resnet18_distance_translation_0_240719	.475
387	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.474
388	deit_small_imagenet_100_seed-0	.474
389	mobilenet_v1_0.25_128	.462
390	my-model	.462
391	mobilenet_v2_0.35_128	.457
392	resnet50_imagenet_10_seed-0	.457
393	mobilenet_v2_1-4_224_pytorch	.455
394	AlexNet_SIN_fov12	.447
395	prednet	.446
396	resnet18-depth_prediction	.443
397	alexnet_training_seed_01_fov4	.442
398	resnet50-cifar	.418
399	alexnet_linf_8_robust	.413
400	alexnet_fov12	.412
401	aughost_fair_resnet18	.410
402	deepeisnn_ei_cifar10_vgg19	.405
403	deepeisnn_ei_cifar10_resnet18	.403
404	alexnet_robust_correct	.399
405	resnet18-contrastive_predictive	.394
406	yudixie_wbh_object_class_scaling_0415_run_2	.389
407	alexnet_fov16	.378
408	AlexNet_SIN_fov16	.374
409	resnet18-autoencoder	.367
410	alexnet_training_seed_02	.366
411	briaai_rmbg_1_4	.364
412	v1-pyr-nodown	.362
413	resnet-152_v2_pytorch	.358
414	resnet50-meshes-lt-100-original-pretrained	.358
415	alexnet_training_seed_06	.356
416	yudixie_wbh_object_class_scaling_0415_run_0	.351
417	alexnet_training_seed_09	.350
418	CORnetZ_CIFAR10	.349
419	alexnet_training_seed_01	.347
420	yudixie_wbh_object_class_scaling_0415_run_1	.346
421	alexnet_training_seed_03	.345
422	resnet50-meshes-lt-100-original-scratch	.345
423	alexnet_training_seed_07	.344
424	alexnet_training_seed_08	.343
425	alexnet_training_seed_10	.342
426	alexnet_training_seed_05	.341
427	resnet50_pretrained_with_retinal_waves	.340
428	CORnetZ_CIFAR10_bs32_20_04	.340
429	alexnet_training_seed_04	.336
430	yudixie_resnet50_random_0_240908	.331
431	mobilevit_small	.330
432	resnet-18_untrained	.329
433	resnet50_FractalDB	.328
434	resnet-50_untrained	.327
435	alexnet_training_seed_01_fov12	.322
436	resnet-50x2_untrained	.321
437	yudixie_wbh_object_class_scaling_0415_run_3	.320
438	yudixie_resnet18_random_0_240719	.317
439	alexnet_training_seed_01_fov16	.304
440	resnet50_imagenet_1_seed-0	.298
441	resnet-18-LC_untrained	.270
442	pr1_stl10_disentangled_alpha04	.215
443	predictive_coding_pc	.189
444	deit_small_imagenet_10_seed-0	.156
445	convnext_small_imagenet_10_seed-0	.121
446	fitvid_trained_on_physion	.117
447	deit_small_imagenet_1_seed-0	.102
448	convnext_small_imagenet_1_seed-0	.092
449	pixels	.075
450	my-model	.075
451	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