A method of video processing comprises performing a conversion between a video unit of a video and a bitstream of the video according to a rule, wherein the rule specifies that whether a cross-component adaptive loop filter (CC-ALF) mode and an adaptive loop filter (ALF) mode are enabled for coding the video unit are indicated in the bitstream in a mutually independent manner.
A method of video processing includes performing a conversion between a video unit of a video and a bitstream of the video according to a rule, wherein the rule specifies whether the bitstream includes at least one of a control flag of a chroma block-based delta pulse code modulation (BDPCM) mode, a palette mode, or an adaptive color transform (ACT) mode is based on a value of a chroma array type of the video.
Usage Of Templates For Decoder-Side Intra Mode Derivation
- Grand Cayman, KY Kai ZHANG - Los Angeles CA, US Li ZHANG - Los Angeles CA, US Yuwen HE - Los Angeles CA, US Hongbin LIU - Beijing, CN
International Classification:
H04N 19/159 H04N 19/176 H04N 19/70 H04N 19/147
Abstract:
Example implementations include a method, apparatus and computer-readable medium of video processing, including constructing, during a conversion between a current video block of a video and a bitstream of the video, at least one template set for the current video block from a plurality of sub-templates. The one or more sub-templates may be selected from a plurality of sub-templates including: a left sub-template, an above sub-template, a right-above sub-template, a left-below sub-template, and a left-above sub-template. The implementations further include deriving at least one intra-prediction mode (IPM) based on cost calculations. The implementations include determining, based on the at least one IPM, a final predictor of the current video block. The implementations include performing the conversion based on the final predictor.
Embodiments of the present disclosure provide methods, apparatuses and computer storage media for video processing. One example method comprises determining, during a conversion between a current video block of a video and a bitstream of the video, a set of motion candidates for the current video block; determining, for each motion candidate in the set of motion candidates, a refined motion candidate by performing a local search around the each motion candidate based on a template matching cost rule; determining, from a set of refined motion candidates generated for the set of motion candidates, a target motion candidate for the current video block; and performing the conversion based on the target motion candidate.
Embodiments of the present disclosure provide methods, apparatuses and computer storage media for video processing. One example method comprises determining, during a conversion between a current video block of a video and a bitstream of the video, at least one set of motion candidates for the current video block, each motion candidate comprising predicted motion information determined from neighboring video blocks of the current video block; determining, based on a template of the current video block and from the at least one set of motion candidates, a target motion candidate for the current video block by using a template matching cost rule; and performing the conversion based on the target motion candidate.
Embodiments of the present disclosure provide methods, apparatuses and computer storage media for video processing. One example method comprises determining, during a conversion between a current video block of a video and a bitstream of the video, a motion candidate for the current video block; refining the motion candidate by performing a local search around the motion candidate based on a template matching cost rule; and performing the conversion based on the refined motion candidate, wherein a search order of the local search is related to a coding mode of the current video block.
Methods And Apparatuses For Cross-Component Prediction
- Grand Cayman, KY Kai Zhang - Los Angeles CA, US Li Zhang - Los Angeles CA, US
International Classification:
H04N 19/132 H04N 19/105 H04N 19/186 H04N 19/176
Abstract:
Example implementations include a method, apparatus and computer-readable medium of video coding, comprising receiving the code block and one or more neighbor samples and determining the value of beta based on at least one of an average chroma value, a midrange chroma value, a median chroma value, an average luma value, a midrange luma value, or a median luma value of two or more neighbor samples.
Methods And Apparatuses For Cross-Component Prediction
- Grand Cayman, KY Kai ZHANG - Los Angeles CA, US Li ZHANG - Los Angeles, US
Assignee:
Lemon Inc. - Grand Cayman
International Classification:
H04N 19/103 H04N 19/176 H04N 19/184 H04N 19/186
Abstract:
Example implementations include a method, apparatus and computer-readable medium of video coding, comprising receiving the code block and one or more neighbor samples and determining the value of beta based on at least one of an average chroma value, a midrange chroma value, a median chroma value, an average luma value, a midrange luma value, or a median luma value of two or more neighbor samples.
Barclays Capital - Greater New York City Area since Jul 2011
Analyst
Nobilis Capital - Greater New York City Area Oct 2010 - Mar 2011
Quant Intern, High Frequency Trading
Ashir Capital - Greater New York City Area May 2010 - Aug 2010
Summer analyst
Education:
New York University 2009 - 2011
MS, Financial Engineering
Nankai University 2005 - 2009
Bacherlor, Financial Engineering
Skills:
C++ R Matlab VBA Options Pricing Market Risk Options Derivatives
Interests:
Systematic Trading, Web Technology, Cloud Computing.
SPI - Porto Area, Portugal since Jan 2012
International Business Consultant
Hellenic Cultural Month - Greater New York City Area May 2011 - May 2012
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David B. Weigle Information Commons, Van-Pelt Dietrich Library - Greater Philadelphia Area Oct 2010 - May 2011
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Teach For China - Greater New York City Area Nov 2010 - Mar 2011
Campus Ambassador
National Committee on U.S.-China Relations - Greater New York City Area Sep 2010 - Dec 2010
Administrative and Program Management Intern
Education:
University of Pennsylvania 2009 - 2011
Master of Science In Education, Intercultural Communication
Shanghai International Studies University 2005 - 2009
Bachelor of Arts, English
Geisinger Medical GroupGeisinger Laboratory Medicine 100 N Academy Ave, Danville, PA 17822 570 271-6338 (phone), 570 271-6105 (fax)
Education:
Medical School Fujian Med Coll, Fuzhou City, Fujian, China Graduated: 1984
Languages:
Chinese English Spanish
Description:
Dr. Zhang graduated from the Fujian Med Coll, Fuzhou City, Fujian, China in 1984. He works in Danville, PA and specializes in Anatomic Pathology & Clinical Pathology. Dr. Zhang is affiliated with Cole Memorial Hospital, Geisinger Medical Center, Geisinger Wyoming Valley Hospital and Geisinger-Shamokin Area Community Hospital.