What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Computer graphics
His scientific interests lie mostly in Artificial intelligence, Computer vision, Texture synthesis, Rendering and Algorithm.
His Artificial intelligence research integrates issues from Specularity and Pattern recognition.
Baining Guo combines subjects such as Surface and Nonlinear programming with his study of Computer vision.
His work carried out in the field of Texture synthesis brings together such families of science as User interface, Texture, Texture mapping, Texture compression and Bidirectional texture function.
He has included themes like Point cloud, Computation, Single view and Parallel computing in his Rendering study.
His research investigates the connection with Algorithm and areas like Solver which intersect with concerns in Computer graphics, Subspace topology and Interpolation.
His most cited work include:
- Real-time texture synthesis by patch-based sampling (589 citations)
- Mesh editing with poisson-based gradient field manipulation (473 citations)
- Real-time KD-tree construction on graphics hardware (375 citations)
What are the main themes of his work throughout his whole career to date?
Baining Guo focuses on Artificial intelligence, Computer vision, Computer graphics, Rendering and Algorithm.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Sample and Pattern recognition.
His Computer vision research is multidisciplinary, incorporating elements of Surface, Computer graphics, Reflectivity and Radiance.
His Computer graphics research focuses on Bidirectional texture function and how it connects with Texture filtering.
The various areas that he examines in his Rendering study include Computation and Ray tracing.
The concepts of his Algorithm study are interwoven with issues in Solver, Mathematical optimization, Texture mapping and Poisson's equation.
He most often published in these fields:
- Artificial intelligence (55.97%)
- Computer vision (50.21%)
- Computer graphics (29.63%)
What were the highlights of his more recent work (between 2012-2021)?
- Artificial intelligence (55.97%)
- Computer vision (50.21%)
- Image (7.41%)
In recent papers he was focusing on the following fields of study:
Baining Guo mainly focuses on Artificial intelligence, Computer vision, Image, Algorithm and Rendering.
His studies in Artificial intelligence integrate themes in fields like Machine learning and Pattern recognition.
His studies deal with areas such as Identity and Computer graphics as well as Computer vision.
His research integrates issues of Point, Geometry, Surface, Expression and Tracking in his study of Image.
His Rendering research is classified as research in Computer graphics.
His Computer graphics research includes elements of Reflection and Solver.
Between 2012 and 2021, his most popular works were:
- Unsupervised Extraction of Video Highlights via Robust Recurrent Auto-Encoders (127 citations)
- Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting (89 citations)
- TopicPanorama: A full picture of relevant topics (72 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
Baining Guo spends much of his time researching Artificial intelligence, Computer vision, Visual analytics, Image and Pattern recognition.
His research brings together the fields of Machine learning and Artificial intelligence.
His research in Computer vision intersects with topics in Shading and Radiance.
Baining Guo focuses mostly in the field of Visual analytics, narrowing it down to matters related to Graph drawing and, in some cases, Information retrieval, Animation, Theoretical computer science and Closeness.
His work in Pattern recognition addresses issues such as Pyramid, which are connected to fields such as Spatial contextual awareness, Pyramid and Inpainting.
His Pixel research includes themes of Encoder, Computational photography, Feature and Semantic feature.
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