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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("SanghaviMurty2020.V4-pls")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	compact_resnet50_robust_V4	.348
2	FrankRobWobv0	.330
3	compact_vgg19_V4	.317
4	compact_resnet50_V4	.295
5	compact_cornets_V4	.293
6	ReAlnet01_cornet_fov4	.273
7	ReAlnet10_cornet	.258
8	efficientnet_b2_imagenet_full	.257
9	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.256
10	cvt_cvt-21-384-in1k_4_LucyV4	.256
11	mobilenet_v2_0_75_224	.256
12	ReAlnet08_cornet	.254
13	konkle_alexnetgn_ipcl_ref01_primary_model	.253
14	effnetb1_272x240	.246
15	ReAlnet05_cornet	.246
16	mobilenet_v2_1_0_192	.245
17	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.245
18	resnet_101_v1	.245
19	compact_cornets_IT	.244
20	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.244
21	inception_v1	.244
22	mobilenet_v2_1_3_224	.243
23	mobilenet_v2_1.0_192-tf	.243
24	resnet101_imagenet_full	.243
25	resnet152_imagenet_full	.243
26	ReAlnet02_cornet	.242
27	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.242
28	ReAlnet03_cornet	.242
29	ReAlnet07_cornet	.241
30	focalnet_tiny_lrf_in1k	.240
31	resnet152_ecoset_full	.240
32	resnet-101_v2-tf	.240
33	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.240
34	ReAlnet01_cornet	.240
35	convnext_large:fb_in22k_ft_in1k	.239
36	deit3_base_patch16_224_fb_in22k_ft_in1k	.239
37	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.239
38	resnet-152_v1-tf	.239
39	ReAlnet04_cornet	.239
40	vit_large_patch14_clip_224:laion2b_ft_in1k	.239
41	resnet-152_v2-tf	.239
42	vision_transformer_vit_large_patch16_224	.239
43	RN50	.239
44	ReAlnet06_cornet	.238
45	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.238
46	grcnn_robust_v1	.237
47	ReAlnet09_cornet	.237
48	omnivore_swinB	.237
49	omnivore_swinS	.237
50	cvt_cvt-21-224-in1k_4_LucyV4	.236
51	convnext_large_clip_laion2b_finelayers	.236
52	cvt_cvt-13-384-in1k_4_LucyV4	.235
53	custom_model_cv_18_dagger_408	.235
54	convnext_tiny:in12k_ft_in1k	.235
55	resnet101_ecoset_full	.235
56	grcnn_v2_text_noise	.235
57	dinov2_vitl14_reg_lc	.234
58	dinov2_vitl14_reg_lc_featread	.234
59	ReAlnet10_ALL	.233
60	mobilenet_v2_1.0_160-tf	.233
61	ReAlnet09_ALL	.233
62	ReAlnet07_ALL	.233
63	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.232
64	vit_base_patch16_clip_224:openai_ft_in1k	.232
65	convnext_femto_ols:d1_in1k	.232
66	convnext_xlarge:fb_in22k_ft_in1k	.232
67	tv_efficientnet-b1	.232
68	ReAlnet04_ALL	.232
69	vit_base_patch16_dinov3-lvd1689m	.231
70	mobilenet_v2_0.75_224-tf	.231
71	vit_large_clip336_openai	.231
72	vit_large_patch14_clip_224:openai_ft_in1k	.231
73	grcnn	.231
74	ReAlnet05_ALL	.231
75	ReAlnet08_ALL	.231
76	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.231
77	ReAlnet01_ALL	.230
78	mobilenet_v2_0.75_192-tf	.230
79	vit_large_patch14_clip_336:laion2b_ft_in1k	.230
80	dinov2_vitg14_lc	.230
81	vit_base_patch14_dinov2-lvd142m	.230
82	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.230
83	ReAlnet02_ALL	.230
84	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.230
85	convnext_tiny_sup	.229
86	ReAlnet03_ALL	.229
87	resnet50_ewconplus_wzc	.229
88	mobilenet_v2_1_0_160	.229
89	omnivore_swinT	.229
90	ReAlnet06_ALL	.228
91	Res2Net50_26w_4s	.228
92	CORnet-S	.228
93	mobilenet_v2_0_75_192	.228
94	cvt_cvt-13-224-in1k_4_LucyV4	.228
95	resnet50_robust_l2_eps1	.227
96	convnext_large_imagenet_full_seed-0	.227
97	vit_base_patch14_reg4_dinov2-lvd142m	.227
98	eva02_large_in22k	.227
99	dinov2_vitl14_lc	.227
100	resnet50_ewconplus_wzc_seed2_2__323	.226
101	mobilenet_v2_0_75_160	.226
102	resnet50_st_wzc_seed7_2_323	.225
103	resnet-50_v2-tf	.225
104	voneresnet-50-non_stochastic	.225
105	xception-keras	.225
106	vonegrcnn_47e	.225
107	mobilenet_v2_1.3_224-tf	.225
108	efficientnet_b0	.225
109	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.224
110	vit_relpos_base_patch16_clsgap_224:sw_in1k	.224
111	inception_v1-tf	.223
112	densenet-121	.223
113	densenet-169-keras	.223
114	resnet50_hvs_wzc	.223
115	mobilenet_v2_0.5_160	.223
116	ViT-B/32	.222
117	AdvProp_efficientnet-b6	.222
118	barlow-twins-resnet50	.222
119	resnet50-VITO-8deg-cc	.222
120	mobilenet_v2_0_5_192	.222
121	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.222
122	mobilenet_v2_1_4_224	.222
123	CLIP_ViT-B_32	.222
124	resnet-101_v1-tf	.221
125	grcnn_109	.221
126	dinov2_vitg14_reg_lc	.220
127	convnext_xxlarge_clip	.220
128	vonegrcnn_52e_full	.220
129	antialias-resnet152	.220
130	mobilenet_v2_1.4_224-tf	.219
131	resnet-18-LC_1st_conv_m	.219
132	inception_v3-tf	.219
133	resnet50_ewconplus_wzc_seed5_2__323	.219
134	inception_v2-tf	.219
135	effnetv2m_custom384	.219
136	resnet50_st_wzc_seed3_2_323	.219
137	resnet50_st_wzc_2	.218
138	vonegrcnn_62e_nobn	.218
139	inception_resnet_v2	.218
140	mobilenet_v2_0_5_224	.217
141	convnext_base:clip_laiona_augreg_ft_in1k_384	.217
142	densenet-201-keras	.217
143	resnet50-vicregl0p9	.216
144	deit_small_imagenet_full_seed-0	.216
145	vgg-19-keras	.216
146	deit_large_imagenet_full_seed-0	.216
147	resnet50_ewconplus_wzc_seed6_2_323	.215
148	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.215
149	deit3_base_patch16_224_fb_in1k	.215
150	vgg-16-keras	.214
151	resnet50_primary_visual_cortex	.214
152	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.214
153	voneresnet-50	.214
154	mobilenet_v2_0.5_192-tf	.213
155	antialiased-rnext101_32x8d	.213
156	AdvProp_efficientnet-b0	.213
157	regnety_032	.212
158	convnext_large_in22k_supervised	.212
159	VOneCORnet-S	.212
160	alexnet_fov4	.212
161	resnext101_32x48d_wsl	.212
162	BiT-M-R50x1	.211
163	inception_v3	.211
164	vonegrcnn_47e	.211
165	resnet-18-LC_w_sh_100_iter_m	.211
166	resnet34_ecoset_full	.211
167	resnet18-instance_recognition	.211
168	cv_18_dagger_408_pretrained	.210
169	resnet50-vitoimagevidnet8	.210
170	AdvProp_efficientnet-b7	.210
171	mobilenet_v2_0.5_224-tf	.210
172	convnext_base_imagenet_full_seed-0	.209
173	resnet-18-LC_w_sh_100_iter_conv_init_m	.209
174	CLIP-RN50	.209
175	mobilenet_v2_1.0_224-tf	.209
176	dinov2_vitl14_lc_res336	.209
177	0.5x_resnet-18_LC	.209
178	yolos_tiny	.208
179	resnet50-moclr8deg	.208
180	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.208
181	resnet50-vicreg	.208
182	AT_efficientnet-b7	.207
183	resnet50-simclr-vissl	.207
184	densenet-121-keras	.206
185	pnasnet_large_halfPrecision	.206
186	resnet50-barlow	.206
187	mobilenet_v2_1_0_224	.206
188	BiT-M-R101x1	.205
189	antialiased-r50	.205
190	pnasnet_large-tf	.205
191	AdvProp_efficientnet-b4	.205
192	0.5x_resnet-18_LC_w_sh_100_iter	.205
193	mobilenet_v1_0.75_224	.205
194	mobilenet_v2_0.75_160-tf	.205
195	ReAlnet01_cornet_fov12	.205
196	resnext101_32x8d_wsl	.205
197	resnet-50-pytorch	.204
198	resnet-50-robust	.204
199	BiT-M-R50x3	.204
200	convnext_small_imagenet_full_seed-0	.204
201	resnet50_imagenet_100_seed-0	.203
202	compact_vgg19_IT	.203
203	resnext101_32x16d_wsl	.203
204	resnet-18-LC_w_sh_1_iter_conv_init_m	.203
205	AlexNet_SIN_fov4	.202
206	0.5x_resnet-18_LC_w_sh_1_iter	.202
207	deit_base_imagenet_full_seed-0	.202
208	resnet18-local_aggregation	.202
209	CORnet-Z	.202
210	mobilenet_v2_0.35_224	.202
211	resnet50-vicregl0p75	.202
212	densenet-201	.202
213	vgg_16	.201
214	resnext101_32x32d_wsl	.201
215	resnet18-relative_position	.201
216	vit_huge_clip336_laion	.201
217	resnet-50_v1-tf	.201
218	resnet18-deepcluster	.201
219	resnet50_random_linf8_perturb	.201
220	resnet-34	.200
221	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.200
222	resnet-18-LC_d_w_sh_1x1_conv_init_m	.200
223	convnext_small_imagenet_100_seed-0	.200
224	resnet-18-LC_w_sh_1_iter_m	.200
225	0.5x_resnet-18_LC_w_sh_10_iter	.199
226	nasnet_mobile	.199
227	resnet50	.199
228	BiT-S-R50x1	.199
229	fixres_resnext101_32x48d_wsl	.199
230	resnet-18-LC_w_sh_10_iter_conv_init_m	.199
231	mobilenet_v1_0.75_128	.198
232	BiT-M-R152x2	.198
233	BiT-M-R101x3	.198
234	resnet50_st_wzc_seed6_2_323	.198
235	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.198
236	resnet18_imagenet21kP	.198
237	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.198
238	mobilenet_v2_0.5_128	.198
239	resnet50_linf_4_robust	.197
240	convnext_tiny_imagenet_full_seed-0	.197
241	mobilenet_v1_1.0_192	.197
242	resnet50-SIN_IN	.197
243	BiT-S-R101x3	.196
244	0.5x_resnet-18	.196
245	CLIP_resnet50	.196
246	CLIP_resnet50_float32	.196
247	mobilenet_v1_1.0_224	.196
248	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.196
249	resnet_SIN_IN_FT_IN	.195
250	resnet50-SIN_IN_IN	.195
251	mobilenet_v1_0.75_192	.195
252	BiT-S-R50x3	.195
253	densenet-169	.195
254	AdvProp_efficientnet-b8	.195
255	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.194
256	resnet-18	.194
257	resnet_50_v1_spiking_l4	.194
258	resnet_50_v1_spiking	.194
259	resnet_50_v1_spiking_l4a	.194
260	resnet50_tutorial	.194
261	resnet_50_v1_spiking_l3	.194
262	resnet50-sup	.194
263	resnet_50_v1	.194
264	yudixie_resnet50_imagenet1kpret_0_240908	.194
265	resnet50_random_l2_perturb	.193
266	resnet50-SIN	.193
267	mobilenet_v1_0.5_128	.193
268	mobilenet_v2_0.35_160	.193
269	BiT-S-R152x2	.192
270	mobilenet_v2_1_0_128	.192
271	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.192
272	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.192
273	resnet-18-LC_m	.191
274	inception_v4-tf	.191
275	nasnet_large-tf	.191
276	mobilenet_v2_0.75_128	.190
277	my-model	.190
278	mobilenet_v1_0.25_224	.190
279	BiT-S-R101x1	.190
280	mobilenet_v1_1.0_160	.189
281	resnet18_ecoset_full	.189
282	nasnet_mobile-tf	.187
283	resnet34_imagenet_full	.187
284	mobilenet_v1_1.0_128	.186
285	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.186
286	resnet18-contrastive_multiview	.186
287	resnet50_imagenet_full	.185
288	alexnet_l2_3_robust	.185
289	resnet-18-LC_w_sh_10_iter_m	.185
290	efficientnet_b1_imagenet_full	.184
291	resnet50_robust_l2_eps3	.184
292	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.183
293	mobilenet_v1_0.25_192	.183
294	mobilenet_v1_0.75_160	.183
295	mobilenet_v1_0.5_224	.183
296	shufflenet_v2_x1_0	.183
297	resnet50_l2_3_robust	.183
298	BiT-M-R152x4	.183
299	alexnet_random_linf8_perturb	.181
300	squeezenet1_1	.181
301	voneresnet-50-robust	.181
302	resnet-18-LC_conv_init_m	.181
303	mobilenet_v1_0.5_192	.181
304	deepeisnn_ei_imagenet_resnet18	.180
305	squeezenet1_0	.180
306	resnet18-supervised	.179
307	resnet18-colorization	.179
308	resnet18_imagenet_full	.179
309	texture_shape_resnet50_trained_on_SIN	.179
310	mobilenet_v2_0.35_192	.179
311	eicircuit_resnet18_bn_20260919	.178
312	imagenet_l2_3_0	.178
313	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.178
314	yudixie_resnet50_object_class_0_240908	.178
315	SWSL_resnet50	.177
316	AdvProp_efficientnet-b2	.177
317	resnet50_linf_8_robust	.177
318	vonealexnet	.177
319	BiT-S-R152x4	.175
320	yudixie_resnet18_distance_translation_rotation_0_240719	.175
321	resnet101	.174
322	regnet_y_400mf	.174
323	resnet18_fair	.174
324	alexnet_random_l2_3_perturb	.173
325	resnet50_ecoset_full	.173
326	r3m_resnet50	.173
327	resnet50_moco_v2	.172
328	AT_efficientnet-b4	.172
329	mobilenet_v1_0.25_160	.172
330	ReAlnet10	.171
331	RN50	.171
332	resnet50_simclr	.171
333	seresnext50_32x4d	.171
334	mobilenet_v2_1.0_128-tf	.171
335	r3m_resnet50_nocrop	.170
336	yudixie_wbh_object_class_scaling_0415_imagenet	.170
337	yudixie_resnet18_imagenet1kpret_0_240719	.170
338	resnet_50_v2	.170
339	mobilenet_v1_0.5_160	.169
340	persistence_memory	.169
341	yudixie_resnet18_distance_translation_0_240719	.169
342	alexnet_training_seed_01_fov4	.169
343	texture_shape_alexnet_trained_on_SIN	.168
344	prednet	.167
345	convnext_base_fb_in22k_ft_in1k	.167
346	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.167
347	persistence_mem	.167
348	resnet-18_test_m	.167
349	deit_small_imagenet_100_seed-0	.166
350	yudixie_resnet18_translation_reg_0_240719	.166
351	vgg_19	.166
352	r3m_resnet18	.165
353	ReAlnet01_cornet_fov16	.165
354	ViT_L_32_imagenet1k	.165
355	yudixie_resnet50_category_class_0_240908	.165
356	alexnet_ks_torevert	.164
357	alexnet	.164
358	yudixie_resnet18_distance_reg_0_240719	.164
359	mobilenet_v2_0.75_96	.164
360	mobilenet_v2_1.0_96	.163
361	ReAlnet08	.163
362	mobilenet_v2_0.35_128	.163
363	AT_efficientnet-b2	.163
364	mobilenet_v1_0.25_128	.162
365	mobilenet_v2_1-4_224_pytorch	.162
366	yudixie_resnet18_object_class_0_240719	.162
367	efficientnet_b0_imagenet_full	.160
368	cornet_s	.160
369	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.160
370	ReAlnet07	.160
371	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.159
372	resnet50_imagenet_10_seed-0	.158
373	ReAlnet06	.158
374	vonealexnet_gaussian_noise_std4_fixed	.158
375	AlexNet_SIN	.157
376	resnet50_byol	.157
377	yudixie_resnet50_translation_rotation_0_240908	.157
378	vggface	.157
379	imagenet_l2_10_0	.156
380	efficientnet-b7	.156
381	artResNet18_1	.156
382	ReAlnet02	.155
383	resnet18-depth_prediction	.155
384	ReAlnet05	.154
385	alexnet_linf_8_robust	.154
386	yudixie_resnet50_distance_translation_0_240908	.154
387	mobilenet_v2_0.35_96	.154
388	yudixie_resnet50_distance_translation_rotation_0_240908	.153
389	mobilenet_v2_0.5_96	.153
390	yudixie_resnet50_translation_reg_0_240908	.152
391	ReAlnet04	.152
392	SWSL_resnext101_32x8d	.152
393	yudixie_resnet18_distance_rotation_0_240719	.152
394	ReAlnet03	.151
395	yudixie_resnet50_distance_rotation_0_240908	.151
396	ReAlnet09	.150
397	resnet18-contrastive_predictive	.150
398	compact_resnet50_IT	.150
399	alexnet_fov12	.149
400	yudixie_resnet18_translation_rotation_0_240719	.149
401	ReAlnet01	.148
402	AlexNet_SIN_fov12	.148
403	yudixie_resnet18_rotation_reg_0_240719	.147
404	convnext_base_fb_in1k	.145
405	convnext_base_fb_in1k_gram_aligned_dinov3	.145
406	r3m_resnet34	.145
407	yudixie_resnet50_distance_reg_0_240908	.145
408	blt_vs	.144
409	alexnet_early_checkpoint	.143
410	yudixie_resnet18_category_class_0_240719	.143
411	yudixie_resnet50_rotation_reg_0_240908	.141
412	alexnet_reduced_aliasing_early_checkpoint	.139
413	alexnet_robust_correct	.138
414	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.135
415	compact_resnet50_robust_IT	.132
416	briaai_rmbg_1_4	.132
417	AlexNet_SIN_fov16	.130
418	deepeisnn_ei_cifar10_resnet18	.129
419	alexnet_fov16	.128
420	gabor_filter_mean_abs_4x4_v2	.124
421	gabor_filter_entropy_4x4_v2	.119
422	gabor_filter_entropy_4x4_v2_forcedCosine	.117
423	v1-pyr-nodown	.112
424	alexnet_training_seed_02	.112
425	deepeisnn_ei_cifar10_vgg19	.111
426	resnet50-cifar	.110
427	alexnet_training_seed_01	.105
428	resnet18-autoencoder	.105
429	CORnetZ_CIFAR10	.104
430	alexnet_training_seed_03	.102
431	alexnet_training_seed_05	.102
432	alexnet_training_seed_01_fov12	.101
433	alexnet_training_seed_08	.100
434	alexnet_training_seed_10	.100
435	alexnet_training_seed_06	.098
436	alexnet_training_seed_09	.098
437	alexnet_training_seed_07	.095
438	yudixie_wbh_object_class_scaling_0415_run_2	.095
439	resnet-50_untrained	.092
440	resnet50_FractalDB	.091
441	resnet50_pretrained_with_retinal_waves	.091
442	resnet-50x2_untrained	.091
443	alexnet_training_seed_04	.089
444	yudixie_wbh_object_class_scaling_0415_run_1	.088
445	alexnet_training_seed_01_fov16	.087
446	resnet-18_untrained	.086
447	yudixie_wbh_object_class_scaling_0415_run_0	.084
448	hmax	.080
449	CORnetZ_CIFAR10_bs32_20_04	.079
450	yudixie_wbh_object_class_scaling_0415_run_3	.074
451	yudixie_resnet18_random_0_240719	.074
452	yudixie_resnet50_random_0_240908	.065
453	resnet50_imagenet_1_seed-0	.063
454	mobilevit_small	.060
455	predictive_coding_pc	.054
456	pr1_stl10_disentangled_alpha04	.050
457	resnet-18-LC_untrained	.049
458	convnext_small_imagenet_10_seed-0	.040
459	gabor_filter_entropy_4x4	.039
460	resnet-152_v2_pytorch	.036
461	convnext_small_imagenet_1_seed-0	.030
462	deit_small_imagenet_10_seed-0	.026
463	deit_small_imagenet_1_seed-0	.020
464	fitvid_trained_on_physion	.020
465	pixels	.014
466	my-model	.013

Benchmark bibtex

@misc{Sanghavi_Murty_DiCarlo_2021,
  title={SanghaviMurty2020},
  url={osf.io/fchme},
  DOI={10.17605/OSF.IO/FCHME},
  publisher={OSF},
  author={Sanghavi, Sachi and Murty, N A R and DiCarlo, James J},
  year={2021},
  month={Nov}
}

Ceiling

0.97.

Note that scores are relative to this ceiling.

Data: SanghaviMurty2020.V4

300 stimuli recordings from 46 sites in V4

Metric: pls