Leaderboard Explore Compare Profile Community Blog FAQ Competition 2024 Report Issue

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	deepeisnn_ei_imagenet_resnet18	1.0
2	ReAlnet09_ALL	1.0
3	ReAlnet10_ALL	1.0
4	ReAlnet04_ALL	1.0
5	ReAlnet03_ALL	1.0
6	ReAlnet01_ALL	1.0
7	ReAlnet08_ALL	1.0
8	yolos_tiny	1.0
9	ReAlnet07_ALL	1.0
10	ReAlnet06_ALL	1.0
11	ReAlnet02_ALL	.994
12	resnet_50_v1_spiking	.955
13	eicircuit_resnet18_bn_20260919	.950
14	ReAlnet05_ALL	.946
15	resnet_50_v1_spiking_l3	.944
16	predictive_coding_pc	.928
17	resnet50-sup	.928
18	resnet_50_v1	.928
19	mobilenet_v2_0_75_160	.928
20	mehrer2020_alexnet_training_seed_01_fov4	.925
21	shufflenet_v2_x1_0	.917
22	mobilenet_v2_0_5_192	.896
23	mobilenet_v2_0_5_224	.893
24	mobilenet_v2_1_0_128	.892
25	alexnet_fov4	.890
26	mobilenet_v2_0_75_192	.886
27	yudixie_wbh_object_class_scaling_0415_imagenet	.886
28	resnet_50_v1_spiking_l4	.878
29	ReAlnet07_cornet	.873
30	ReAlnet07	.873
31	deepeisnn_ei_cifar10_resnet18	.867
32	resnet_SIN_IN_FT_IN	.858
33	deit_small_imagenet_100_seed-0	.850
34	ReAlnet09_cornet	.832
35	ReAlnet09	.832
36	ReAlnet10_cornet	.832
37	ReAlnet10	.832
38	resnet_101_v1	.831
39	vit_large_patch14_clip_224:openai_ft_in1k	.826
40	vonegrcnn_62e_nobn	.823
41	pnasnet_large_halfPrecision	.822
42	resnet_50_v1_spiking_l4a	.821
43	yudixie_resnet18_random_0_240719	.820
44	ReAlnet01_cornet_fov4	.818
45	ReAlnet08_cornet	.813
46	ReAlnet08	.813
47	ReAlnet01_cornet	.808
48	ReAlnet01	.808
49	VOneCORnet-S	.804
50	vonegrcnn_47e	.803
51	ReAlnet03_cornet	.798
52	ReAlnet03	.798
53	densenet_201_pytorch	.794
54	vonegrcnn_52e_full	.793
55	resnet50-SIN_IN_IN	.785
56	resnet-18_test_m	.763
57	ReAlnet06_cornet	.759
58	ReAlnet06	.759
59	antialias-resnet152	.753
60	ReAlnet02_cornet	.753
61	ReAlnet02	.753
62	ReAlnet05_cornet	.751
63	ReAlnet05	.751
64	gabor_filter_mean_abs_4x4_v2	.749
65	yudixie_resnet18_imagenet1kpret_0_240719	.748
66	yudixie_resnet50_imagenet1kpret_0_240908	.743
67	ReAlnet04_cornet	.738
68	ReAlnet04	.738
69	mobilenet_v2_1_0_160	.737
70	resnet50_tutorial	.736
71	vgg_19	.729
72	compact_cornets_V4	.710
73	grcnn	.708
74	effnetb1_272x240	.708
75	compact_cornets_IT	.695
76	resnet50_st_wzc_seed6_2_323	.689
77	hmax	.684
78	resnet50_imagenet_100_seed-0	.679
79	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.678
80	mobilenet_v2_1_0_224	.677
81	deit_small_imagenet_full_seed-0	.669
82	resnet50_primary_visual_cortex	.668
83	compact_resnet50_robust_IT	.665
84	convnext_xlarge:fb_in22k_ft_in1k	.665
85	antialiased-r50	.662
86	resnet50_robust_l2_eps1	.651
87	vgg_16	.645
88	convnext_tiny:in12k_ft_in1k	.640
89	yudixie_wbh_object_class_scaling_0415_run_1	.634
90	mobilenet_v2_1_4_224	.632
91	mobilenet_v2_1-4_224_pytorch	.632
92	resnet50_untrained_linhead	.631
93	Res2Net50_26w_4s	.630
94	artResNet18_1	.626
95	yudixie_wbh_object_class_scaling_0415_run_2	.622
96	convnext_large_in22k_supervised	.607
97	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.607
98	yudixie_resnet50_random_0_240908	.603
99	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.600
100	yudixie_resnet18_category_class_0_240719	.598
101	ReAlnet01_cornet_fov12	.596
102	deit3_base_patch16_224_fb_in22k_ft_in1k	.587
103	yudixie_resnet50_object_class_0_240908	.586
104	resnet50_ewconplus_wzc_seed2_2__323	.583
105	alexnet_training_seed_03	.571
106	alexnet_training_seed_01_fov4	.569
107	ReAlnet01_cornet_fov16	.568
108	deepeisnn_ei_cifar10_vgg19	.565
109	resnet50_st_wzc_seed3_2_323	.564
110	yudixie_resnet50_distance_translation_rotation_0_240908	.562
111	alexnet_training_seed_01_fov16	.562
112	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.562
113	yudixie_wbh_object_class_scaling_0415_run_3	.561
114	resnet18_fair	.560
115	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.559
116	resnet50_hvs_wzc	.556
117	convnext_small_imagenet_10_seed-0	.555
118	alexnet_training_seed_10	.555
119	convnext_large:fb_in22k_ft_in1k	.553
120	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.553
121	resnet50_imagenet_full	.552
122	mehrer2020_alexnet_training_seed_05	.548
123	resnet18_ecoset_full	.547
124	inception_v4	.546
125	gabor_filter_entropy_4x4	.543
126	yudixie_wbh_object_class_scaling_0415_run_0	.541
127	mobilenet_v2_1_0_192	.541
128	vit_base_patch16_clip_224:openai_ft_in1k	.540
129	resnet18_imagenet21kP	.538
130	voneresnet-50	.535
131	regnet_y_400mf	.533
132	deit_small_imagenet_1_seed-0	.533
133	alexnet_training_seed_01	.530
134	voneresnet-50-non_stochastic	.529
135	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.524
136	resnet50-vitoimagevidnet8	.520
137	resnet50-VITO-8deg-cc	.520
138	mehrer2020_alexnet_training_seed_01	.517
139	alexnet_training_seed_07	.516
140	nasnet_large	.513
141	efficientnet_b2_imagenet_full	.508
142	yudixie_resnet18_translation_rotation_0_240719	.508
143	gabor_filter_entropy_4x4_v2_forcedCosine	.504
144	resnet50_ewconplus_wzc_seed6_2_323	.502
145	resnet50_st_wzc_2	.502
146	alexnet_training_seed_08	.502
147	resnet_152_v1	.500
148	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.498
149	yudixie_resnet50_category_class_0_240908	.498
150	resnet50_ewconplus_wzc	.497
151	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.496
152	deit_base_imagenet_full_seed-0	.496
153	resnet152_imagenet_full	.495
154	alexnet_training_seed_01_fov12	.494
155	BiT-S-R50x3	.490
156	resnet50_imagenet_10_seed-0	.490
157	mehrer2020_alexnet_training_seed_10	.488
158	alexnet_training_seed_09	.488
159	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.487
160	resnet50_st_wzc_seed7_2_323	.486
161	yudixie_resnet50_distance_rotation_0_240908	.486
162	mehrer2020_alexnet_training_seed_09	.483
163	AlexNet_SIN_fov4	.482
164	compact_vgg19_IT	.482
165	mehrer2020_alexnet_training_seed_04	.481
166	convnext_femto_ols:d1_in1k	.480
167	mehrer2020_alexnet_training_seed_07	.476
168	compact_resnet50_V4	.475
169	resnet50-SIN_IN	.473
170	alexnet_training_seed_06	.473
171	vit_relpos_base_patch16_clsgap_224:sw_in1k	.472
172	persistence_memory	.465
173	alexnet_ks_torevert	.460
174	alexnet	.460
175	compact_vgg19_V4	.459
176	alexnet_fov16	.456
177	compact_resnet50_robust_V4	.454
178	persistence_mem	.453
179	efficientnet_b0_imagenet_full	.453
180	AlexNet_SIN_fov16	.453
181	mobilenet_v2_1_3_224	.452
182	alexnet_training_seed_04	.450
183	alexnet_fov12	.448
184	gabor_filter_entropy_4x4_v2	.446
185	alexnet_training_seed_05	.444
186	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.441
187	vonealexnet	.440
188	nasnet_mobile	.438
189	briaai_rmbg_1_4	.437
190	densenet-201	.436
191	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.436
192	convnext_small_imagenet_100_seed-0	.435
193	AlexNet_SIN_fov12	.431
194	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.430
195	deit_large_imagenet_full_seed-0	.428
196	cvt_cvt-21-384-in1k_4_LucyV4	.424
197	yudixie_resnet18_rotation_reg_0_240719	.419
198	yudixie_resnet18_object_class_0_240719	.418
199	alexnet_training_seed_02	.418
200	vit_large_patch14_clip_224:laion2b_ft_in1k	.416
201	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.412
202	resnet_152_v2	.410
203	densenet-169	.409
204	resnet34_ecoset_full	.407
205	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.407
206	resnet18_imagenet_full	.406
207	convnext_base_fb_in22k_ft_in1k	.406
208	densenet-121	.403
209	mehrer2020_alexnet_training_seed_06	.400
210	convnext_small_imagenet_full_seed-0	.395
211	mehrer2020_alexnet_training_seed_03	.393
212	xception	.392
213	pr1_stl10_disentangled_alpha04	.387
214	pnasnet_large_pytorch	.381
215	convnext_large_imagenet_full_seed-0	.375
216	resnet50-SIN	.371
217	resnet50_ewconplus_wzc_seed5_2__323	.367
218	deit_small_imagenet_10_seed-0	.365
219	yudixie_resnet50_distance_translation_0_240908	.365
220	resnet101_imagenet_full	.362
221	mehrer2020_alexnet_training_seed_08	.360
222	resnet50_imagenet_1_seed-0	.358
223	mehrer2020_alexnet_training_seed_02	.358
224	BiT-S-R101x3	.355
225	inception_v1	.351
226	AT_efficientnet-b2	.348
227	AdvProp_efficientnet-b2	.348
228	mehrer2020_alexnet_training_seed_01_fov12	.348
229	resnext101_32x16d_wsl	.346
230	mehrer2020_alexnet_training_seed_01_fov16	.346
231	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.345
232	imagenet_l2_3_0	.341
233	resnet50_robust_l2_eps3	.341
234	yudixie_resnet50_translation_rotation_0_240908	.341
235	cvt_cvt-13-224-in1k_4_LucyV4	.340
236	yudixie_resnet18_distance_rotation_0_240719	.337
237	ViT_L_32_imagenet1k	.331
238	yudixie_resnet18_translation_reg_0_240719	.326
239	tv_efficientnet-b1	.326
240	yudixie_resnet50_translation_reg_0_240908	.324
241	inception_v3	.324
242	yudixie_resnet18_distance_translation_rotation_0_240719	.323
243	AlexNet_SIN	.322
244	convnext_large_clip_laion2b_finelayers	.317
245	AdvProp_efficientnet-b8	.315
246	resnet152_ecoset_full	.314
247	compact_resnet50_IT	.312
248	resnet-50-robust	.305
249	ijepa_vith14_linhead	.305
250	yudixie_resnet18_distance_translation_0_240719	.302
251	resnet50_ijepacnn_linhead	.300
252	resnet101_ecoset_full	.298
253	convnext_base_fb_in1k	.293
254	efficientnet_b1_imagenet_full	.289
255	resnet50_ecoset_full	.287
256	blt_vs	.284
257	AdvProp_efficientnet-b7	.281
258	dinov2_vitl14_reg_lc	.280
259	yudixie_resnet50_distance_reg_0_240908	.280
260	efficientnet-b7	.277
261	convnext_base:clip_laiona_augreg_ft_in1k_384	.270
262	BiT-S-R101x1	.270
263	inception_v3_pytorch	.262
264	convnext_base_fb_in1k_gram_aligned_dinov3	.258
265	dinov2_vitl14_lc	.257
266	cvt_cvt-13-384-in1k_4_LucyV4	.255
267	cv_18_dagger_408_pretrained	.249
268	AdvProp_efficientnet-b4	.247
269	resnet50_simclr_linhead_01norm	.242
270	vith14_untrained_linhead	.239
271	resnet_101_v2	.239
272	voneresnet-50-robust	.238
273	yudixie_resnet50_rotation_reg_0_240908	.232
274	grcnn_109	.227
275	resnext101_32x32d_wsl	.220
276	resnet-152_v2_pytorch	.212
277	dinov2_vitg14_lc	.209
278	resnet50_simsiam_linhead	.206
279	AdvProp_efficientnet-b6	.206
280	efficientnet_b0	.197
281	BiT-S-R50x1	.195
282	resnext101_32x8d_wsl	.195
283	convnext_tiny_imagenet_full_seed-0	.194
284	resnet34_imagenet_full	.192
285	resnet_50_v2	.189
286	convnext_small_imagenet_1_seed-0	.186
287	vit_large_patch14_clip_336:laion2b_ft_in1k	.183
288	regnety_032	.179
289	BiT-S-R152x2	.175
290	yudixie_resnet18_distance_reg_0_240719	.167
291	resnet50_eMMCR_Vanilla	.164
292	vit_base_patch16_dinov3-lvd1689m	.163
293	convnext_base_imagenet_full_seed-0	.162
294	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.156
295	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.152
296	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.138
297	resnet50-vicregl0p9	.123
298	resnet50_cpc_linhead	.113
299	resnext101_32x48d_wsl	.106
300	cvt_cvt-21-224-in1k_4_LucyV4	.100
301	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.098
302	focalnet_tiny_lrf_in1k	.092
303	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.085
304	resnet50_byol_linhead	.073
305	deit3_base_patch16_224_fb_in1k	.065
306	convnext_tiny_sup	.062
307	seresnext50_32x4d	.060
308	resnet50_supervised_linhead	.057
309	resnet50_vicreg_linhead	.045
310	resnet50_barlowtwins_linhead	.020
311	resnet50-vicreg	.019
312	resnet50-vicregl0p75	.000
313	resnet50-moclr8deg	.000
314	resnet50-barlow	.000
315	vith14_supervised_linhead
316	dinov2_vitl14_reg_lc_featread
317	dinov2_vitl14_lc_res336
318	eva02_large_in22k
319	dinov2_vitg14_reg_lc
320	vit_base_patch14_reg4_dinov2-lvd142m
321	vit_base_patch14_dinov2-lvd142m
322	pnasnet_large
323	mobilenet_v2_0_75_224
324	custom_model_cv_18_dagger_408
325	vit_huge_clip336_laion
326	convnext_xxlarge_clip
327	vit_large_clip336_openai
328	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k
329	omnivore_swinS
330	omnivore_swinB
331	BiT-S-R152x4
332	MIM
333	TAU
334	SimVP
335	PredRNN
336	ConvLSTM
337	antialiased-rnext101_32x8d

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

0.54.

Note that scores are relative to this ceiling.

Data: Maniquet2024

Metric: confusion_similarity