Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Maniquet2024-confusion_similarity")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	yolos_tiny	1.0
2	resnet_50_v1_spiking	.955
3	resnet_50_v1_spiking_l3	.944
4	resnet_50_v1	.928
5	mobilenet_v2_0_75_160	.928
6	shufflenet_v2_x1_0	.917
7	mobilenet_v2_1_0_128	.892
8	resnet_50_v1_spiking_l4	.878
9	ReAlnet07	.873
10	ReAlnet07_cornet	.873
11	resnet_SIN_IN_FT_IN	.858
12	deit_small_imagenet_100_seed-0	.850
13	ReAlnet09	.832
14	ReAlnet09_cornet	.832
15	ReAlnet10_cornet	.832
16	ReAlnet10	.832
17	resnet_101_v1	.831
18	vit_large_patch14_clip_224:openai_ft_in1k	.826
19	vonegrcnn_62e_nobn	.823
20	resnet_50_v1_spiking_l4a	.821
21	yudixie_resnet18_random_0_240719	.820
22	ReAlnet08	.813
23	ReAlnet08_cornet	.813
24	ReAlnet01_cornet	.808
25	ReAlnet01	.808
26	VOneCORnet-S	.804
27	vonegrcnn_47e	.803
28	ReAlnet03	.798
29	ReAlnet03_cornet	.798
30	densenet_201_pytorch	.794
31	vonegrcnn_52e_full	.793
32	resnet50-SIN_IN_IN	.785
33	resnet-18_test_m	.763
34	ReAlnet06_cornet	.759
35	ReAlnet06	.759
36	antialias-resnet152	.753
37	ReAlnet02_cornet	.753
38	ReAlnet02	.753
39	ReAlnet05_cornet	.751
40	ReAlnet05	.751
41	yudixie_resnet18_imagenet1kpret_0_240719	.748
42	yudixie_resnet50_imagenet1kpret_0_240908	.743
43	ReAlnet04	.738
44	ReAlnet04_cornet	.738
45	mobilenet_v2_1_0_160	.737
46	resnet50_tutorial	.736
47	vgg_19	.729
48	grcnn	.708
49	effnetb1_272x240	.708
50	resnet50_imagenet_100_seed-0	.679
51	mobilenet_v2_1_0_224	.677
52	deit_small_imagenet_full_seed-0	.669
53	resnet50_primary_visual_cortex	.668
54	convnext_xlarge:fb_in22k_ft_in1k	.665
55	antialiased-r50	.662
56	resnet50_robust_l2_eps1	.651
57	vgg_16	.645
58	convnext_tiny:in12k_ft_in1k	.640
59	mobilenet_v2_1_4_224	.632
60	mobilenet_v2_1-4_224_pytorch	.632
61	Res2Net50_26w_4s	.630
62	artResNet18_1	.626
63	yudixie_resnet50_random_0_240908	.603
64	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.600
65	yudixie_resnet18_category_class_0_240719	.598
66	yudixie_resnet50_object_class_0_240908	.586
67	alexnet_training_seed_03	.571
68	yudixie_resnet50_distance_translation_rotation_0_240908	.562
69	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.562
70	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.559
71	convnext_small_imagenet_10_seed-0	.555
72	alexnet_training_seed_10	.555
73	convnext_large:fb_in22k_ft_in1k	.553
74	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.553
75	resnet18_ecoset_full	.547
76	inception_v4	.546
77	vit_base_patch16_clip_224:openai_ft_in1k	.540
78	resnet18_imagenet21kP	.538
79	voneresnet-50	.535
80	regnet_y_400mf	.533
81	deit_small_imagenet_1_seed-0	.533
82	alexnet_training_seed_01	.530
83	voneresnet-50-non_stochastic	.529
84	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.524
85	resnet50-vitoimagevidnet8	.520
86	resnet50-VITO-8deg-cc	.520
87	alexnet_training_seed_07	.516
88	nasnet_large	.513
89	efficientnet_b2_imagenet_full	.508
90	yudixie_resnet18_translation_rotation_0_240719	.508
91	alexnet_training_seed_08	.502
92	resnet_152_v1	.500
93	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.498
94	yudixie_resnet50_category_class_0_240908	.498
95	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.496
96	deit_base_imagenet_full_seed-0	.496
97	resnet152_imagenet_full	.495
98	resnet50_imagenet_10_seed-0	.490
99	alexnet_training_seed_09	.488
100	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.487
101	yudixie_resnet50_distance_rotation_0_240908	.486
102	convnext_femto_ols:d1_in1k	.480
103	resnet50-SIN_IN	.473
104	alexnet_training_seed_06	.473
105	vit_relpos_base_patch16_clsgap_224:sw_in1k	.472
106	alexnet_ks_torevert	.460
107	efficientnet_b0_imagenet_full	.453
108	alexnet_training_seed_04	.450
109	alexnet_training_seed_05	.444
110	nasnet_mobile	.438
111	briaai_rmbg_1_4	.437
112	densenet-201	.436
113	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.436
114	convnext_small_imagenet_100_seed-0	.435
115	deit_large_imagenet_full_seed-0	.428
116	cvt_cvt-21-384-in1k_4_LucyV4	.424
117	yudixie_resnet18_rotation_reg_0_240719	.419
118	yudixie_resnet18_object_class_0_240719	.418
119	alexnet_training_seed_02	.418
120	vit_large_patch14_clip_224:laion2b_ft_in1k	.416
121	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.412
122	resnet_152_v2	.410
123	resnet34_ecoset_full	.407
124	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.407
125	convnext_small_imagenet_full_seed-0	.395
126	xception	.392
127	pnasnet_large_pytorch	.381
128	convnext_large_imagenet_full_seed-0	.375
129	resnet50-SIN	.371
130	deit_small_imagenet_10_seed-0	.365
131	yudixie_resnet50_distance_translation_0_240908	.365
132	resnet101_imagenet_full	.362
133	resnet50_imagenet_1_seed-0	.358
134	inception_v1	.351
135	AdvProp_efficientnet-b2	.348
136	AT_efficientnet-b2	.348
137	resnext101_32x16d_wsl	.346
138	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.345
139	resnet50_robust_l2_eps3	.341
140	imagenet_l2_3_0	.341
141	yudixie_resnet50_translation_rotation_0_240908	.341
142	cvt_cvt-13-224-in1k_4_LucyV4	.340
143	yudixie_resnet18_distance_rotation_0_240719	.337
144	yudixie_resnet18_translation_reg_0_240719	.326
145	tv_efficientnet-b1	.326
146	yudixie_resnet50_translation_reg_0_240908	.324
147	inception_v3	.324
148	yudixie_resnet18_distance_translation_rotation_0_240719	.323
149	AlexNet_SIN	.322
150	resnet152_ecoset_full	.314
151	resnet-50-robust	.305
152	yudixie_resnet18_distance_translation_0_240719	.302
153	resnet101_ecoset_full	.298
154	efficientnet_b1_imagenet_full	.289
155	resnet50_ecoset_full	.287
156	blt_vs	.284
157	yudixie_resnet50_distance_reg_0_240908	.280
158	efficientnet-b7	.277
159	BiT-S-R101x1	.270
160	inception_v3_pytorch	.262
161	cvt_cvt-13-384-in1k_4_LucyV4	.255
162	AdvProp_efficientnet-b4	.247
163	resnet_101_v2	.239
164	voneresnet-50-robust	.238
165	yudixie_resnet50_rotation_reg_0_240908	.232
166	grcnn_109	.227
167	resnext101_32x32d_wsl	.220
168	resnet-152_v2_pytorch	.212
169	AdvProp_efficientnet-b6	.206
170	efficientnet_b0	.197
171	BiT-S-R50x1	.195
172	resnext101_32x8d_wsl	.195
173	convnext_tiny_imagenet_full_seed-0	.194
174	resnet_50_v2	.189
175	convnext_small_imagenet_1_seed-0	.186
176	yudixie_resnet18_distance_reg_0_240719	.167
177	resnet50_eMMCR_Vanilla	.164
178	convnext_base_imagenet_full_seed-0	.162
179	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.156
180	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.138
181	resnet50-vicregl0p9	.123
182	resnext101_32x48d_wsl	.106
183	cvt_cvt-21-224-in1k_4_LucyV4	.100
184	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.098
185	focalnet_tiny_lrf_in1k	.092
186	convnext_tiny_sup	.062
187	resnet50-vicreg	.019
188	resnet50-vicregl0p75	-0.002
189	resnet50-moclr8deg	-0.009
190	resnet50-barlow	-0.065
191	BiT-S-R50x3
192	convnext_xxlarge:clip_laion2b_soup_ft_in1k
193	vit_large_patch14_clip_336:openai_ft_in12k_in1k
194	mobilenet_v2_1_0_192
195	omnivore_swinS
196	mobilenet_v2_1_3_224
197	AdvProp_efficientnet-b8
198	BiT-S-R152x4
199	mobilenet_v2_0_75_192
200	BiT-S-R101x3
201	BiT-S-R152x2
202	mobilenet_v2_0_5_224
203	mobilenet_v2_0_5_192
204	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k
205	omnivore_swinB
206	pnasnet_large
207	custom_model_cv_18_dagger_408
208	densenet-169
209	hmax
210	densenet-121
211	antialiased-rnext101_32x8d
212	PredRNN
213	ViT_L_32_imagenet1k
214	MIM
215	TAU
216	convnext_base:clip_laiona_augreg_ft_in1k_384
217	SimVP
218	resnet50-sup
219	ConvLSTM
220	vit_large_patch14_clip_336:laion2b_ft_in1k
221	AdvProp_efficientnet-b7
222	mobilenet_v2_0_75_224
223	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384

Benchmark bibtex

@article {Maniquet2024.04.02.587669,
	author = {Maniquet, Tim and de Beeck, Hans Op and Costantino, Andrea Ivan},
	title = {Recurrent issues with deep neural network models of visual recognition},
	elocation-id = {2024.04.02.587669},
	year = {2024},
	doi = {10.1101/2024.04.02.587669},
	publisher = {Cold Spring Harbor Laboratory},
	URL = {https://www.biorxiv.org/content/early/2024/04/10/2024.04.02.587669},
	eprint = {https://www.biorxiv.org/content/early/2024/04/10/2024.04.02.587669.full.pdf},
	journal = {bioRxiv}
}

Ceiling

Not available

Data: Maniquet2024

Metric: confusion_similarity