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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	.360
2	FrankRobWobv0	.342
3	compact_vgg19_V4	.328
4	compact_resnet50_V4	.306
5	compact_cornets_V4	.304
6	ReAlnet10_cornet	.267
7	efficientnet_b2_imagenet_full	.266
8	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.265
9	cvt_cvt-21-384-in1k_4_LucyV4	.265
10	mobilenet_v2_0_75_224	.264
11	ReAlnet08_cornet	.263
12	konkle_alexnetgn_ipcl_ref01_primary_model	.261
13	effnetb1_272x240	.254
14	ReAlnet05_cornet	.254
15	mobilenet_v2_1_0_192	.253
16	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.253
17	resnet_101_v1	.253
18	compact_cornets_IT	.252
19	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.252
20	inception_v1	.252
21	mobilenet_v2_1_3_224	.252
22	mobilenet_v2_1.0_192-tf	.252
23	resnet101_imagenet_full	.252
24	resnet152_imagenet_full	.251
25	ReAlnet02_cornet	.250
26	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.250
27	ReAlnet03_cornet	.250
28	ReAlnet07_cornet	.250
29	focalnet_tiny_lrf_in1k	.249
30	resnet152_ecoset_full	.249
31	resnet-101_v2-tf	.248
32	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.248
33	ReAlnet01_cornet	.248
34	convnext_large:fb_in22k_ft_in1k	.248
35	resnet-152_v1-tf	.247
36	ReAlnet04_cornet	.247
37	vit_large_patch14_clip_224:laion2b_ft_in1k	.247
38	resnet-152_v2-tf	.247
39	vision_transformer_vit_large_patch16_224	.247
40	RN50	.247
41	ReAlnet06_cornet	.246
42	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.246
43	grcnn_robust_v1	.246
44	ReAlnet09_cornet	.245
45	omnivore_swinB	.245
46	omnivore_swinS	.245
47	cvt_cvt-21-224-in1k_4_LucyV4	.245
48	cvt_cvt-13-384-in1k_4_LucyV4	.244
49	custom_model_cv_18_dagger_408	.243
50	convnext_tiny:in12k_ft_in1k	.243
51	resnet101_ecoset_full	.243
52	grcnn_v2_text_noise	.243
53	ReAlnet10_ALL	.241
54	mobilenet_v2_1.0_160-tf	.241
55	ReAlnet09_ALL	.241
56	ReAlnet07_ALL	.241
57	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.240
58	vit_base_patch16_clip_224:openai_ft_in1k	.240
59	convnext_femto_ols:d1_in1k	.240
60	convnext_xlarge:fb_in22k_ft_in1k	.240
61	tv_efficientnet-b1	.240
62	ReAlnet04_ALL	.240
63	mobilenet_v2_0.75_224-tf	.239
64	vit_large_patch14_clip_224:openai_ft_in1k	.239
65	grcnn	.239
66	ReAlnet05_ALL	.239
67	ReAlnet08_ALL	.239
68	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.239
69	ReAlnet01_ALL	.238
70	mobilenet_v2_0.75_192-tf	.238
71	vit_large_patch14_clip_336:laion2b_ft_in1k	.238
72	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.238
73	ReAlnet02_ALL	.238
74	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.238
75	convnext_tiny_sup	.237
76	ReAlnet03_ALL	.237
77	resnet50_ewconplus_wzc	.237
78	mobilenet_v2_1_0_160	.237
79	omnivore_swinT	.237
80	ReAlnet06_ALL	.236
81	Res2Net50_26w_4s	.236
82	CORnet-S	.236
83	mobilenet_v2_0_75_192	.236
84	cvt_cvt-13-224-in1k_4_LucyV4	.236
85	resnet50_robust_l2_eps1	.235
86	convnext_large_imagenet_full_seed-0	.235
87	mobilenet_v2_0_75_160	.234
88	resnet-50_v2-tf	.233
89	voneresnet-50-non_stochastic	.233
90	xception-keras	.233
91	vonegrcnn_47e	.233
92	mobilenet_v2_1.3_224-tf	.233
93	efficientnet_b0	.233
94	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.232
95	vit_relpos_base_patch16_clsgap_224:sw_in1k	.231
96	inception_v1-tf	.231
97	densenet-121	.231
98	densenet-169-keras	.231
99	mobilenet_v2_0.5_160	.230
100	ViT-B/32	.230
101	AdvProp_efficientnet-b6	.230
102	barlow-twins-resnet50	.230
103	resnet50-VITO-8deg-cc	.230
104	mobilenet_v2_0_5_192	.230
105	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.229
106	mobilenet_v2_1_4_224	.229
107	CLIP_ViT-B_32	.229
108	resnet-101_v1-tf	.229
109	grcnn_109	.229
110	vonegrcnn_52e_full	.228
111	antialias-resnet152	.227
112	mobilenet_v2_1.4_224-tf	.227
113	resnet-18-LC_1st_conv_m	.227
114	inception_v3-tf	.227
115	inception_v2-tf	.227
116	effnetv2m_custom384	.227
117	vonegrcnn_62e_nobn	.226
118	inception_resnet_v2	.226
119	mobilenet_v2_0_5_224	.224
120	convnext_base:clip_laiona_augreg_ft_in1k_384	.224
121	densenet-201-keras	.224
122	resnet50-vicregl0p9	.224
123	deit_small_imagenet_full_seed-0	.224
124	vgg-19-keras	.224
125	deit_large_imagenet_full_seed-0	.223
126	vgg-16-keras	.222
127	resnet50_primary_visual_cortex	.222
128	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.221
129	voneresnet-50	.221
130	mobilenet_v2_0.5_192-tf	.221
131	antialiased-rnext101_32x8d	.221
132	AdvProp_efficientnet-b0	.220
133	VOneCORnet-S	.219
134	resnext101_32x48d_wsl	.219
135	BiT-M-R50x1	.219
136	inception_v3	.219
137	vonegrcnn_47e	.219
138	resnet-18-LC_w_sh_100_iter_m	.218
139	resnet34_ecoset_full	.218
140	resnet18-instance_recognition	.218
141	cv_18_dagger_408_pretrained	.218
142	resnet50-vitoimagevidnet8	.218
143	AdvProp_efficientnet-b7	.218
144	mobilenet_v2_0.5_224-tf	.217
145	convnext_base_imagenet_full_seed-0	.217
146	resnet-18-LC_w_sh_100_iter_conv_init_m	.216
147	CLIP-RN50	.216
148	mobilenet_v2_1.0_224-tf	.216
149	0.5x_resnet-18_LC	.216
150	yolos_tiny	.215
151	resnet50-moclr8deg	.215
152	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.215
153	resnet50-vicreg	.215
154	AT_efficientnet-b7	.215
155	resnet50-simclr-vissl	.214
156	densenet-121-keras	.214
157	resnet50-barlow	.213
158	mobilenet_v2_1_0_224	.213
159	BiT-M-R101x1	.213
160	antialiased-r50	.212
161	pnasnet_large-tf	.212
162	AdvProp_efficientnet-b4	.212
163	0.5x_resnet-18_LC_w_sh_100_iter	.212
164	mobilenet_v1_0.75_224	.212
165	mobilenet_v2_0.75_160-tf	.212
166	resnext101_32x8d_wsl	.212
167	resnet-50-pytorch	.211
168	resnet-50-robust	.211
169	BiT-M-R50x3	.211
170	convnext_small_imagenet_full_seed-0	.211
171	resnet50_imagenet_100_seed-0	.210
172	compact_vgg19_IT	.210
173	resnext101_32x16d_wsl	.210
174	resnet-18-LC_w_sh_1_iter_conv_init_m	.210
175	0.5x_resnet-18_LC_w_sh_1_iter	.209
176	deit_base_imagenet_full_seed-0	.209
177	resnet18-local_aggregation	.209
178	CORnet-Z	.209
179	mobilenet_v2_0.35_224	.209
180	resnet50-vicregl0p75	.209
181	densenet-201	.208
182	vgg_16	.208
183	resnext101_32x32d_wsl	.208
184	resnet18-relative_position	.208
185	resnet-50_v1-tf	.208
186	resnet18-deepcluster	.208
187	resnet50_random_linf8_perturb	.208
188	resnet-34	.207
189	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.207
190	resnet-18-LC_d_w_sh_1x1_conv_init_m	.207
191	convnext_small_imagenet_100_seed-0	.207
192	resnet-18-LC_w_sh_1_iter_m	.207
193	0.5x_resnet-18_LC_w_sh_10_iter	.206
194	nasnet_mobile	.206
195	resnet50	.206
196	BiT-S-R50x1	.206
197	fixres_resnext101_32x48d_wsl	.206
198	resnet-18-LC_w_sh_10_iter_conv_init_m	.206
199	mobilenet_v1_0.75_128	.205
200	BiT-M-R152x2	.205
201	BiT-M-R101x3	.205
202	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.205
203	resnet18_imagenet21kP	.204
204	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.204
205	mobilenet_v2_0.5_128	.204
206	resnet50_linf_4_robust	.204
207	convnext_tiny_imagenet_full_seed-0	.204
208	mobilenet_v1_1.0_192	.204
209	resnet50-SIN_IN	.204
210	BiT-S-R101x3	.203
211	0.5x_resnet-18	.203
212	CLIP_resnet50	.203
213	CLIP_resnet50_float32	.203
214	mobilenet_v1_1.0_224	.203
215	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.202
216	resnet50-SIN_IN_IN	.202
217	resnet_SIN_IN_FT_IN	.202
218	mobilenet_v1_0.75_192	.202
219	BiT-S-R50x3	.202
220	densenet-169	.202
221	AdvProp_efficientnet-b8	.202
222	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.201
223	resnet-18	.201
224	resnet_50_v1_spiking_l4	.200
225	resnet_50_v1_spiking	.200
226	resnet_50_v1_spiking_l4a	.200
227	resnet50_tutorial	.200
228	resnet_50_v1_spiking_l3	.200
229	resnet50-sup	.200
230	resnet_50_v1	.200
231	yudixie_resnet50_imagenet1kpret_0_240908	.200
232	resnet50_random_l2_perturb	.200
233	resnet50-SIN	.200
234	mobilenet_v1_0.5_128	.199
235	mobilenet_v2_0.35_160	.199
236	BiT-S-R152x2	.199
237	mobilenet_v2_1_0_128	.199
238	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.198
239	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.198
240	resnet-18-LC_m	.198
241	inception_v4-tf	.198
242	nasnet_large-tf	.198
243	mobilenet_v2_0.75_128	.197
244	my-model	.197
245	mobilenet_v1_0.25_224	.196
246	BiT-S-R101x1	.196
247	mobilenet_v1_1.0_160	.195
248	resnet18_ecoset_full	.195
249	nasnet_mobile-tf	.194
250	resnet34_imagenet_full	.194
251	mobilenet_v1_1.0_128	.193
252	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.192
253	resnet18-contrastive_multiview	.192
254	resnet50_imagenet_full	.192
255	alexnet_l2_3_robust	.192
256	resnet-18-LC_w_sh_10_iter_m	.192
257	efficientnet_b1_imagenet_full	.191
258	resnet50_robust_l2_eps3	.190
259	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.190
260	mobilenet_v1_0.25_192	.190
261	mobilenet_v1_0.75_160	.189
262	mobilenet_v1_0.5_224	.189
263	shufflenet_v2_x1_0	.189
264	resnet50_l2_3_robust	.189
265	BiT-M-R152x4	.189
266	alexnet_random_linf8_perturb	.187
267	squeezenet1_1	.187
268	voneresnet-50-robust	.187
269	resnet-18-LC_conv_init_m	.187
270	mobilenet_v1_0.5_192	.187
271	squeezenet1_0	.186
272	resnet18-supervised	.185
273	resnet18-colorization	.185
274	resnet18_imagenet_full	.185
275	texture_shape_resnet50_trained_on_SIN	.185
276	mobilenet_v2_0.35_192	.185
277	imagenet_l2_3_0	.184
278	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.184
279	yudixie_resnet50_object_class_0_240908	.184
280	SWSL_resnet50	.184
281	AdvProp_efficientnet-b2	.183
282	resnet50_linf_8_robust	.183
283	BiT-S-R152x4	.181
284	yudixie_resnet18_distance_translation_rotation_0_240719	.181
285	resnet101	.180
286	regnet_y_400mf	.180
287	alexnet_random_l2_3_perturb	.179
288	resnet50_ecoset_full	.179
289	r3m_resnet50	.179
290	resnet50_moco_v2	.178
291	AT_efficientnet-b4	.178
292	mobilenet_v1_0.25_160	.178
293	ReAlnet10	.177
294	RN50	.177
295	resnet50_simclr	.177
296	mobilenet_v2_1.0_128-tf	.176
297	r3m_resnet50_nocrop	.176
298	yudixie_resnet18_imagenet1kpret_0_240719	.176
299	resnet_50_v2	.175
300	mobilenet_v1_0.5_160	.175
301	yudixie_resnet18_distance_translation_0_240719	.175
302	texture_shape_alexnet_trained_on_SIN	.174
303	alexnet	.174
304	prednet	.173
305	resnet-18_test_m	.173
306	deit_small_imagenet_100_seed-0	.172
307	yudixie_resnet18_translation_reg_0_240719	.172
308	vgg_19	.171
309	r3m_resnet18	.171
310	ViT_L_32_imagenet1k	.171
311	yudixie_resnet50_category_class_0_240908	.171
312	alexnet_ks_torevert	.170
313	alexnet	.170
314	alexnet-baseline	.170
315	alexnet	.170
316	alexnet	.170
317	alexnet	.170
318	alexnet	.170
319	alexnet	.170
320	alexnet	.170
321	alexnet	.170
322	yudixie_resnet18_distance_reg_0_240719	.169
323	mobilenet_v2_0.75_96	.169
324	mobilenet_v2_1.0_96	.169
325	ReAlnet08	.169
326	mobilenet_v2_0.35_128	.169
327	AT_efficientnet-b2	.169
328	mobilenet_v1_0.25_128	.168
329	mobilenet_v2_1-4_224_pytorch	.168
330	yudixie_resnet18_object_class_0_240719	.167
331	efficientnet_b0_imagenet_full	.166
332	cornet_s	.166
333	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.165
334	ReAlnet07	.165
335	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.164
336	resnet50_imagenet_10_seed-0	.164
337	ReAlnet06	.163
338	resnet50	.163
339	vonealexnet_gaussian_noise_std4_fixed	.163
340	AlexNet_SIN	.163
341	resnet50_byol	.163
342	yudixie_resnet50_translation_rotation_0_240908	.163
343	vggface	.162
344	imagenet_l2_10_0	.162
345	efficientnet-b7	.162
346	artResNet18_1	.162
347	ReAlnet02	.160
348	resnet18-depth_prediction	.160
349	ReAlnet05	.159
350	alexnet_linf_8_robust	.159
351	yudixie_resnet50_distance_translation_0_240908	.159
352	mobilenet_v2_0.35_96	.159
353	yudixie_resnet50_distance_translation_rotation_0_240908	.158
354	mobilenet_v2_0.5_96	.158
355	yudixie_resnet50_translation_reg_0_240908	.158
356	ReAlnet04	.157
357	SWSL_resnext101_32x8d	.157
358	yudixie_resnet18_distance_rotation_0_240719	.157
359	ReAlnet03	.157
360	yudixie_resnet50_distance_rotation_0_240908	.156
361	ReAlnet09	.156
362	resnet18-contrastive_predictive	.155
363	compact_resnet50_IT	.155
364	yudixie_resnet18_translation_rotation_0_240719	.154
365	ReAlnet01	.154
366	yudixie_resnet18_rotation_reg_0_240719	.152
367	r3m_resnet34	.150
368	yudixie_resnet50_distance_reg_0_240908	.150
369	blt_vs	.149
370	resnet50-meshes-lt-100-original-pretrained	.148
371	alexnet_early_checkpoint	.148
372	yudixie_resnet18_category_class_0_240719	.148
373	yudixie_resnet50_rotation_reg_0_240908	.146
374	alexnet_reduced_aliasing_early_checkpoint	.144
375	alexnet_robust_correct	.143
376	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.140
377	compact_resnet50_robust_IT	.137
378	briaai_rmbg_1_4	.136
379	resnet50-meshes-lt-100-original-scratch	.135
380	v1-pyr-nodown	.116
381	alexnet_training_seed_02	.116
382	resnet50-cifar	.114
383	alexnet_training_seed_01	.108
384	resnet18-autoencoder	.108
385	CORnetZ_CIFAR10	.108
386	alexnet_training_seed_03	.105
387	alexnet_training_seed_05	.105
388	alexnet_training_seed_08	.103
389	alexnet_training_seed_10	.103
390	alexnet_training_seed_06	.101
391	alexnet_training_seed_09	.101
392	alexnet_training_seed_07	.098
393	resnet-50_untrained	.095
394	resnet50_FractalDB	.094
395	resnet50_pretrained_with_retinal_waves	.094
396	resnet-50x2_untrained	.094
397	alexnet_training_seed_04	.092
398	resnet-18_untrained	.089
399	hmax	.083
400	CORnetZ_CIFAR10_bs32_20_04	.081
401	yudixie_resnet18_random_0_240719	.076
402	yudixie_resnet50_random_0_240908	.068
403	resnet50_imagenet_1_seed-0	.065
404	mobilevit_small	.062
405	resnet-18-LC_untrained	.051
406	convnext_small_imagenet_10_seed-0	.042
407	resnet-152_v2_pytorch	.037
408	convnext_small_imagenet_1_seed-0	.031
409	deit_small_imagenet_10_seed-0	.027
410	deit_small_imagenet_1_seed-0	.021
411	fitvid_trained_on_physion	.021
412	pixels	.015
413	my-model	.013
414	efficientnet-b0
415	efficientnet-b6
416	efficientnet-b2
417	efficientnet-b4
418	AT_efficientnet-b0
419	resnet18-simclr
420	openclip
421	resnet50_ImageNet
422	yudixie_resnet50_imagenet1kpret_0_240312
423	resnet_152_v1
424	ConvLSTM
425	PredRNN
426	SimVP
427	TAU
428	MIM
429	densenet_201_pytorch
430	pnasnet_large_pytorch
431	inception_v3_pytorch
432	inception_v4
433	xception
434	nasnet_large
435	pnasnet_large
436	resnet_101_v2
437	vonegrcnn_62e_nobn
438	resnet_152_v2
439	vonegrcnn_52e_full

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