https://s4nyam.github.io/panodiff/assets/data/challenge.js?v=2

1/* PanoDiff challenge: 300-image pool (150 real from DENTEX, 150 synthetic from seven generators), every image
2   passing the same sharpness and noise gate as good 1024 x 512 DENTEX radiographs. How the images were chosen is
3   described on the page (section 1, 'How the images were chosen'). The pool is lightly scrambled so the answers
4   are not readable at a glance. */
5window.PDS_CHALLENGE = {
6 "v": 2,
7 "firebase": {
8  "apiKey": "AIzaSyDft2dBw97fmtRqovy6zlf7M9eCeV2uhqg",
9  "authDomain": "panodiff-42e4a.firebaseapp.com",
10  "projectId": "panodiff-42e4a",
11  "storageBucket": "panodiff-42e4a.firebasestorage.app",
12  "messagingSenderId": "84748237765",
13  "appId": "1:84748237765:web:2d79c8dd15f46e9daae9ac"
14 },
15 "models": {
16  "pdsr": {
17   "name": "PanoDiff-SR",
18   "family": "diffusion",
19   "about": "Ours: DDIM diffusion at 256 x 128, then fine-tuned HAT super-resolution to 1024 x 512.",
20   "n": 44
21  },
22  "fg_hat": {
23   "name": "FastGAN + HAT-SR",
24   "family": "GAN",
25   "about": "A lightweight GAN at 256 x 128, upscaled by the same HAT model.",
26   "n": 10
27  },
28  "sg2ada": {
29   "name": "StyleGAN2-ADA",
30   "family": "GAN",
31   "about": "Trained from scratch directly at 1024 x 512 (Karras et al., 2020).",
32   "n": 16
33  },
34  "sg3": {
35   "name": "StyleGAN3",
36   "family": "GAN",
37   "about": "Alias-free StyleGAN3-T, trained from scratch at 1024 x 512 (Karras et al., 2021).",
38   "n": 32
39  },
40  "adm": {
41   "name": "ADM",
42   "family": "diffusion",
43   "about": "Pixel-space diffusion (Dhariwal & Nichol, 2021) trained directly at 1024 x 512.",
44   "n": 24
45  },
46  "ldm": {
47   "name": "Latent diffusion",
48   "family": "diffusion",
49   "about": "A latent diffusion model following Medfusion (Mueller-Franzes et al., 2023).",
50   "n": 12
51  },
52  "pdhr": {
53   "name": "PanoDiff-HR",
54   "family": "diffusion",
55   "about": "Our U-Net widened to generate the full 1024 x 512 image in one step.",
56   "n": 12
57  },
58  "dentex": {
59   "name": "DENTEX (real)",
60   "family": "real",
61   "about": "Real panoramic radiographs from the public DENTEX challenge dataset (CC BY-NC-SA 4.0).",
62   "n": 150
63  }
64 },
65 "strata": {
66  "s_study": 3,
67  "s_sg3": 32,
68  "s_sg2ada": 16,
69  "s_adm": 24,
70  "s_ldm": 12,
71  "s_pdhr": 12,
72  "s_fg_hat": 10,
73  "s_pdsr": 41,
74  "r_study": 7,
75  "r_hard": 60,
76  "r_typical": 83
77 },
78 "observers": [
79  "EC1",
80  "EC2",
81  "EC3",
82  "EP1",
83  "EP2",
84  "EP3"
85 ],
86 "pool": "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87};