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

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