Xu Jizheng

What is he best known for?

The fields of study he is best known for:

• Artificial intelligence
• Computer vision
• Algorithm

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Coding tree unit, Multiview Video Coding and Context-adaptive binary arithmetic coding. His research investigates the connection between Artificial intelligence and topics such as Pattern recognition that intersect with issues in Image coding and Pixel. His Computer vision study frequently involves adjacent topics like Convolutional neural network.

The various areas that Xu Jizheng examines in his Coding tree unit study include Speedup and Parallel computing. His studies in Multiview Video Coding integrate themes in fields like Computer engineering and Sub-band coding. His Context-adaptive binary arithmetic coding study deals with Real-time computing intersecting with Transcoding, Computer hardware, Algorithm and Scalable Video Coding.

His most cited work include:

• AOD-Net: All-in-One Dehazing Network (391 citations)
• Efficient Parallel Framework for HEVC Motion Estimation on Many-Core Processors (344 citations)
• A Highly Parallel Framework for HEVC Coding Unit Partitioning Tree Decision on Many-core Processors (322 citations)

What are the main themes of his work throughout his whole career to date?

Xu Jizheng focuses on Artificial intelligence, Computer vision, Video processing, Algorithm and Bitstream. His Artificial intelligence study combines topics from a wide range of disciplines, such as Coding tree unit and Pattern recognition. His Coding tree unit research incorporates elements of Multiview Video Coding, Sub-band coding and Context-adaptive binary arithmetic coding.

His work in the fields of Computer vision, such as Motion compensation, Data compression and Wavelet, overlaps with other areas such as Visual media. His study in Video processing is interdisciplinary in nature, drawing from both Digital video, Representation and Motion vector. His biological study spans a wide range of topics, including Real-time computing, Algorithmic efficiency and Affine transformation.

He most often published in these fields:

• Artificial intelligence (55.15%)
• Computer vision (45.92%)
• Video processing (42.06%)

What were the highlights of his more recent work (between 2019-2021)?

• Video processing (42.06%)
• Bitstream (34.55%)
• Artificial intelligence (55.15%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Video processing, Bitstream, Artificial intelligence, Computer vision and Algorithm. His research integrates issues of Digital video, Representation and Motion vector in his study of Video processing. His Bitstream research includes themes of Buffer, Residual, Scaling and Affine transformation.

His Artificial intelligence course of study focuses on Decoding methods and Encoding. His Computer vision study combines topics in areas such as Representation and Coding tree unit. His study in the fields of Quantization under the domain of Algorithm overlaps with other disciplines such as Component and Set.

Between 2019 and 2021, his most popular works were:

• Intra-picture prediction using non-adjacent reference lines of sample values (23 citations)
• Universal Adversarial Perturbations Generative Network For Speaker Recognition (6 citations)
• Direct Speech-to-Image Translation (5 citations)

In his most recent research, the most cited papers focused on:

• Artificial intelligence
• Algorithm
• Computer vision

Xu Jizheng mainly focuses on Video processing, Artificial intelligence, Representation, Computer vision and Bitstream. His Video processing research is multidisciplinary, relying on both Decoding methods, Encoding and Sample. Xu Jizheng studied Artificial intelligence and Luma that intersect with Frame.

Xu Jizheng combines subjects such as Current, Algorithm, Motion vector, Block and Scaling with his study of Representation. His Computer vision research is multidisciplinary, incorporating elements of Representation and Resampling. His research integrates issues of Motion and Pulse-code modulation in his study of Bitstream.