id
processing priority
3
site type
0 (generic, awaiting analysis)
review version
11
html import
20 (imported)
first seen date
2025-02-15 05:12:09
expired found date
-
created at
2025-02-15 05:12:09
updated at
2025-02-15 05:12:10
length
18
crc
19728
tld
86
nm parts
0
nm random digits
0
nm rare letters
0
is subdomain of id
87719371 (github.io)
previous id
0
replaced with id
0
related id
-
dns primary id
0
dns alternative id
0
lifecycle status
0 (unclassified, or currently active)
deleted subdomains
0
page imported products
0
page imported random
0
page imported parking
0
count skipped due to recent timeouts on the same server IP
0
count content received but rejected due to 11-799
0
count dns errors
0
count cert errors
0
count timeouts
0
count http 429
0
count http 404
0
count http 403
0
count http 5xx
0
next operation date
-
server bits
—
server ip
-
mp import status
20
mp rejected date
-
mp saved date
-
mp size orig
11218
mp size raw text
3931
mp inner links count
0
mp inner links status
1 (no links)
title
description
image
site name
author
updated
2026-02-18 18:55:26
raw text
DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformer DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformer Wei-Ting Chen 1,2 Gurunandan Krishnan 2 Qiang Gao 2 Sy-Yen Kuo 1 Sizhuo Ma 2* Jian Wang 2*◆ 1 National Taiwan University, 2 Snap Inc. * Co-corresponding authors ◆ Project Lead (CVPR 2024) Paper arXiv Code Data Abstract Generic Face Image Quality Assessment (GFIQA) evaluates the perceptual quality of facial images, which is crucial in improving image restoration algorithms and selecting high-quality face images for downstream tasks. We present a novel transformer-based method for GFIQA, which is aided by two unique mechanisms. First, a novel Dual-Set Degradation Representation Learning (DSL) mechanism uses facial images with both synthetic and real degradations to decouple degradation from content, ensuring generalizability to re...
redirect type
0 (-)
block type
0 (no issues)
detected language
1 (English)
category id
Pozostałe (16)
index version
1
spam phrases
0
text nonlatin
0
text cyrillic
0
text characters
3183
text words
527
text unique words
277
text lines
47
text sentences
20
text paragraphs
5
text words per sentence
26
text matched phrases
0
text matched dictionaries
0
links self subdomains
0
links other subdomains
3 - homepage.ntu.edu.tw, sizhuoma.netlify.app, openaccess.thecvf.com
links other domains
0
links spam adult
0
links spam random
0
links spam expired
0
links ext activities
1
links ext ecommerce
0
links ext finance
0
links ext crypto
0
links ext booking
0
links ext news
0
links ext leaks
0
links ext ugc
links ext klim
0
links ext generic
1
dol status
0
dol updated
2026-02-18 18:55:26
rss path
rss status
1 (priority 1 already searched, no matches found)
rss found date
-
rss size orig
0
rss items
0
rss spam phrases
0
rss detected language
0 (awaiting analysis)
inbefore feed id
-
inbefore status
0 (new)
sitemap path
sitemap status
1 (priority 1 already searched, no matches found)
sitemap review version
2
sitemap urls count
0
sitemap urls adult
0
sitemap filtered products
0
sitemap filtered videos
0
sitemap found date
-
sitemap process date
-
sitemap first import date
-
sitemap last import date
-