id
processing priority
3
site type
5 (wiki-type site, growing by topic rather than chronologically)
review version
11
html import
20 (imported)
first seen date
2024-09-14 15:45:39
expired found date
-
created at
2024-09-14 15:45:39
updated at
2024-09-17 05:30:55
length
19
crc
24325
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
13936
mp size raw text
4262
mp inner links count
0
mp inner links status
1 (no links)
title
DGInStyle Data Pipeline
description
DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control
image
site name
author
updated
2026-02-22 14:58:17
raw text
DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control ECCV 2024 Yuru Jia 1,2 , Lukas Hoyer 1 , Shengyu Huang 1 , Tianfu Wang 1 , Luc Van Gool 1,2,3 , Konrad Schindler 1 , Anton Obukhov 1 1 ETH Zurich, 2 KU Leuven, 3 INSAIT Sofia Paper Generation Code Segmentation Code Generated Data 🤗 Model DGInStyle is a data generation pipeline designed for domain-generalizable semantic segmentation. Abstract Large, pretrained latent diffusion models (LDMs) have demonstrated an extraordinary ability to generate creative content, specialize to user data through few-shot fine-tuning, and condition their output on other modalities, such as semantic maps. However, are they usable as large-scale data generators, e.g., to improve tasks in the perception...
redirect type
0 (-)
block type
0 (no issues)
detected language
1 (English)
category id
index version
1
spam phrases
0
text nonlatin
0
text cyrillic
0
text characters
3150
text words
544
text unique words
263
text lines
73
text sentences
25
text paragraphs
5
text words per sentence
21
text matched phrases
0
text matched dictionaries
0
links self subdomains
0
links other subdomains
0
links other domains
1 - obukhov.ai
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
8 - drive.google.com
links ext klim
0
links ext generic
3
dol status
0
dol updated
2026-02-22 14:58:17
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
-