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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("BMD2024.dotted_1Behavioral-accuracy_distance")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
2	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.983
3	vit_large_patch14_clip_224:openai_ft_in1k	.801
4	resnext101_32x48d_wsl	.770
5	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
6	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.697
7	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.655
8	vit_large_patch14_clip_336:laion2b_ft_in1k	.655
9	resnext101_32x8d_wsl	.655
10	resnext101_32x16d_wsl	.603
11	convnext_base:clip_laiona_augreg_ft_in1k_384	.582
12	resnext101_32x32d_wsl	.510
13	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.478
14	convnext_large:fb_in22k_ft_in1k	.447
15	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.437
16	convnext_xlarge:fb_in22k_ft_in1k	.354
17	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.354
18	densenet-201	.343
19	densenet_201_pytorch	.343
20	resnet50-SIN	.322
21	convnext_base_imagenet_full_seed-0	.312
22	grcnn_109	.312
23	AdvProp_efficientnet-b4	.302
24	AdvProp_efficientnet-b2	.302
25	BiT-S-R152x2	.302
26	AT_efficientnet-b2	.302
27	AdvProp_efficientnet-b7	.291
28	effnetb1_272x240	.281
29	resnet_101_v1	.281
30	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.270
31	focalnet_tiny_lrf_in1k	.260
32	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.250
33	AdvProp_efficientnet-b6	.250
34	regnet_y_400mf	.250
35	ReAlnet04	.239
36	resnet101_imagenet_full	.239
37	AlexNet_SIN	.239
38	convnext_large_imagenet_full_seed-0	.239
39	ReAlnet03	.229
40	ReAlnet07	.229
41	resnet50_imagenet_full	.229
42	resnet50_tutorial	.229
43	resnet_50_v1_spiking_l4a	.229
44	convnext_small_imagenet_full_seed-0	.229
45	antialias-resnet152	.229
46	resnet152_imagenet_full	.229
47	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.229
48	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.229
49	resnet34_imagenet_full	.229
50	resnet_50_v1	.229
51	voneresnet-50	.229
52	ReAlnet01	.229
53	resnet50-sup	.229
54	AdvProp_efficientnet-b8	.229
55	blt_vs	.218
56	resnet50-SIN_IN_IN	.218
57	Res2Net50_26w_4s	.218
58	resnet_SIN_IN_FT_IN	.218
59	ReAlnet06	.208
60	ReAlnet09	.208
61	convnext_small_imagenet_100_seed-0	.208
62	resnet50-SIN_IN	.208
63	resnet50_robust_l2_eps1	.208
64	ReAlnet02	.208
65	ReAlnet05	.208
66	mobilenet_v2_1_0_192	.198
67	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.198
68	resnet_50_v1_spiking	.187
69	ReAlnet10	.187
70	alexnet	.187
71	mobilenet_v2_0_75_192	.187
72	alexnet_ks_torevert	.187
73	AlexNet_SIN_fov4	.187
74	voneresnet-50-robust	.187
75	antialiased-r50	.187
76	BiT-S-R50x3	.187
77	BiT-S-R152x4	.187
78	mobilenet_v2_1_0_128	.177
79	ReAlnet08	.177
80	efficientnet_b0_imagenet_full	.177
81	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.177
82	resnet18_imagenet_full	.177
83	nasnet_mobile	.177
84	resnet50-moclr8deg	.177
85	densenet-121	.177
86	resnet50_eMMCR_Vanilla	.166
87	vit_base_patch16_clip_224:openai_ft_in1k	.166
88	cvt_cvt-13-224-in1k_4_LucyV4	.166
89	pnasnet_large	.166
90	resnet_152_v1	.166
91	convnext_tiny:in12k_ft_in1k	.156
92	inception_v3	.156
93	alexnet_fov4	.156
94	voneresnet-50-non_stochastic	.156
95	inception_v4	.156
96	resnet50-VITO-8deg-cc	.156
97	resnet50-vitoimagevidnet8	.156
98	BiT-S-R101x3	.156
99	densenet-169	.156
100	deit_small_imagenet_full_seed-0	.146
101	resnet50_ewconplus_wzc	.146
102	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.146
103	mobilenet_v2_0_75_160	.146
104	pnasnet_large_pytorch	.146
105	cvt_cvt-13-384-in1k_4_LucyV4	.146
106	nasnet_large	.146
107	mobilenet_v2_1_0_224	.146
108	mobilenet_v2_1_3_224	.146
109	AlexNet_SIN_fov16	.146
110	mobilenet_v2_0_5_192	.135
111	tv_efficientnet-b1	.135
112	convnext_tiny_imagenet_full_seed-0	.135
113	grcnn	.135
114	convnext_tiny_sup	.135
115	ViT_L_32_imagenet1k	.125
116	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.125
117	inception_v3_pytorch	.125
118	cvt_cvt-21-384-in1k_4_LucyV4	.125
119	vit_relpos_base_patch16_clsgap_224:sw_in1k	.125
120	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.125
121	inception_v1	.125
122	BiT-S-R101x1	.125
123	alexnet_training_seed_03	.125
124	resnet_50_v1_spiking_l4	.114
125	mobilenet_v2_0_5_224	.114
126	resnet50_imagenet_100_seed-0	.114
127	deit_large_imagenet_full_seed-0	.114
128	deit_small_imagenet_100_seed-0	.114
129	shufflenet_v2_x1_0	.114
130	BiT-S-R50x1	.114
131	resnet50-vicregl0p75	.114
132	resnet_50_v2	.114
133	resnet50_imagenet_10_seed-0	.104
134	alexnet_training_seed_05	.104
135	alexnet_training_seed_06	.104
136	alexnet_training_seed_02	.104
137	alexnet_training_seed_04	.104
138	cv_18_dagger_408_pretrained	.104
139	cvt_cvt-21-224-in1k_4_LucyV4	.104
140	alexnet_training_seed_10	.104
141	alexnet_training_seed_08	.104
142	convnext_small_imagenet_1_seed-0	.104
143	custom_model_cv_18_dagger_408	.104
144	resnet-50-robust	.104
145	bp_resnet50_julios	.104
146	resnet-152_v2_pytorch	.104
147	resnet50_imagenet_1_seed-0	.104
148	deit_small_imagenet_10_seed-0	.104
149	efficientnet_b2_imagenet_full	.104
150	convnext_small_imagenet_10_seed-0	.104
151	deit_base_imagenet_full_seed-0	.104
152	alexnet_fov16	.104
153	deit_small_imagenet_1_seed-0	.104
154	resnet_50_v1_spiking_l3	.104
155	vgg_16	.104
156	efficientnet_b0	.104
157	resnet50-barlow	.104
158	resnet_101_v2	.104
159	vonegrcnn_62e_nobn	.104
160	resnet_152_v2	.104
161	vonegrcnn_47e	.104
162	alexnet_training_seed_01_fov16	.104
163	vonegrcnn_52e_full	.104
164	imagenet_l2_3_0	.104
165	resnet50_robust_l2_eps3	.104
166	alexnet_training_seed_09	.104
167	mobilenet_v2_0_75_224	.094
168	mobilenet_v2_1_0_160	.094
169	alexnet_fov12	.094
170	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.094
171	artResNet18_1	.094
172	mobilenet_v2_1-4_224_pytorch	.083
173	alexnet_training_seed_07	.083
174	efficientnet_b1_imagenet_full	.083
175	vgg_19	.083
176	mobilenet_v2_1_4_224	.083
177	alexnet_training_seed_01_fov4	.083
178	resnet50-vicregl0p9	.083
179	convnext_femto_ols:d1_in1k	.083
180	alexnet_training_seed_01	.073
181	AlexNet_SIN_fov12	.073
182	alexnet_training_seed_01_fov12	.062
183	xception	.042
184	resnet101_ecoset_full
185	ReAlnet03_ALL
186	ReAlnet07_ALL
187	resnet50_ecoset_full
188	yolos_tiny
189	yudixie_resnet50_category_class_0_240908
190	yudixie_resnet18_category_class_0_240719
191	yudixie_resnet50_distance_reg_0_240908
192	briaai_rmbg_1_4
193	ReAlnet01_cornet
194	hmax
195	resnet18_imagenet21kP
196	ConvLSTM
197	PredRNN
198	SimVP
199	TAU
200	MIM
201	antialiased-rnext101_32x8d
202	ReAlnet02_cornet
203	compact_resnet50_V4
204	ReAlnet03_cornet
205	yudixie_resnet50_distance_rotation_0_240908
206	resnet18_ecoset_full
207	ReAlnet04_cornet
208	resnet34_ecoset_full
209	ReAlnet01_cornet_fov4
210	compact_resnet50_IT
211	yudixie_resnet50_rotation_reg_0_240908
212	compact_resnet50_robust_V4
213	yudixie_resnet50_translation_reg_0_240908
214	ReAlnet01_cornet_fov12
215	resnet152_ecoset_full
216	yudixie_resnet18_distance_translation_0_240719
217	ReAlnet05_cornet
218	yudixie_resnet18_translation_rotation_0_240719
219	yudixie_resnet18_distance_rotation_0_240719
220	compact_vgg19_V4
221	resnet-18_test_m
222	yudixie_resnet50_distance_translation_0_240908
223	yudixie_resnet18_random_0_240719
224	yudixie_resnet18_cat_obj_class_all_latents_0_240719
225	yudixie_resnet18_distance_translation_rotation_0_240719
226	ReAlnet06_cornet
227	yudixie_resnet18_object_class_0_240719
228	yudixie_resnet18_rotation_reg_0_240719
229	yudixie_resnet18_imagenet1kpret_0_240719
230	yudixie_resnet18_translation_reg_0_240719
231	yudixie_resnet18_distance_reg_0_240719
232	efficientnet-b7
233	ReAlnet01_cornet_fov16
234	compact_vgg19_IT
235	ReAlnet07_cornet
236	yudixie_resnet50_translation_rotation_0_240908
237	ReAlnet01_ALL
238	ReAlnet08_cornet
239	VOneCORnet-S
240	omnivore_swinB
241	resnet50-vicreg
242	ReAlnet09_cornet
243	ReAlnet02_ALL
244	compact_cornets_V4
245	ReAlnet04_ALL
246	omnivore_swinS
247	compact_cornets_IT
248	ReAlnet05_ALL
249	ReAlnet10_cornet
250	yudixie_resnet50_cat_obj_class_all_latents_0_240908
251	yudixie_resnet50_imagenet1kpret_0_240908
252	ReAlnet06_ALL
253	yudixie_resnet50_random_0_240908
254	compact_resnet50_robust_IT
255	yudixie_resnet50_distance_translation_rotation_0_240908
256	yudixie_resnet50_object_class_0_240908
257	ReAlnet08_ALL
258	ReAlnet09_ALL
259	resnet50_primary_visual_cortex
260	ReAlnet10_ALL

Benchmark bibtex

None

Ceiling

0.98.

Note that scores are relative to this ceiling.

Data: BMD2024.dotted_1Behavioral

Metric: accuracy_distance