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
2024-08-28 10:43:06
expired found date
-
created at
2024-08-28 10:43:05
updated at
2024-08-29 15:19:56
length
33
crc
5021
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
10783
mp size raw text
2918
mp inner links count
0
mp inner links status
1 (no links)
title
description
image
site name
author
updated
2026-01-28 10:47:39
raw text
Learning to Autofocus Learning to Autofocus Charles Herrmann Richard Strong Bowen Neal Wadhwa Rahul Garg Qiurui He Jonathan T. Barron Ramin Zabih Google Research | Paper | Dataset Capture | Samples of RGB and Depth | Dataset | Left: Our Dataset. We provide a realistic dataset of 510 focal stacks captured "in the wild" along with a computed depth from SFM on 5 different views. These focal stacks have a large variation in color, texture, scene elements, and depth. Middle: Our Problem Formulation. We define Autofocus as three different problems: single-slice where the algorithm receives a single capture at a random starting point and then estimates the most in-focus index; focal stack where the algorithm receives the full focal stack and then estimates the most in-focus index; and two-step where the algorithm receives a single capture at a random starting point but can then pick the next index to capture, then the algorithm uses these two cap...
redirect type
0 (-)
block type
0 (no issues)
detected language
1 (English)
category id
Other [en] (231)
index version
2025123101
spam phrases
0
text nonlatin
0
text cyrillic
0
text characters
2257
text words
434
text unique words
233
text lines
51
text sentences
19
text paragraphs
3
text words per sentence
22
text matched phrases
0
text matched dictionaries
0
links self subdomains
0
links other subdomains
links other domains
links spam adult
0
links spam random
0
links spam expired
0
links ext activities
2
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
1 - linkedin.com
links ext klim
0
links ext generic
2
dol status
0
dol updated
2026-01-28 10:47:39
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
1
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
-