Min Sun mainly investigates Artificial intelligence, Computer vision, Pose, Pattern recognition and Object. His Artificial intelligence research incorporates elements of Machine learning, Adaptation and Natural language processing. His Adaptation research focuses on subjects like Adversarial system, which are linked to Image.
When carried out as part of a general Computer vision research project, his work on Image processing, Image-based modeling and rendering and Markov random field is frequently linked to work in Markov process and Depth perception, therefore connecting diverse disciplines of study. Min Sun focuses mostly in the field of Pose, narrowing it down to topics relating to Object detection and, in certain cases, Object model. His study in the fields of Object detector under the domain of Object overlaps with other disciplines such as Cinematography.
His primary scientific interests are in Artificial intelligence, Computer vision, Machine learning, Pattern recognition and Image. Object, Equirectangular projection, Segmentation, Object detection and Pose are among the areas of Artificial intelligence where Min Sun concentrates his study. Min Sun has included themes like Object model, Inference and Branch and bound in his Pose study.
In his works, Min Sun conducts interdisciplinary research on Computer vision and Depth perception. Other disciplines of study, such as Supervised learning and Markov random field, are mixed together with his Depth perception studies. His work focuses on many connections between Pattern recognition and other disciplines, such as Depth map, that overlap with his field of interest in Feature.
Min Sun focuses on Artificial intelligence, Computer vision, Equirectangular projection, Benchmark and Image. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Pattern recognition. His studies in Machine learning integrate themes in fields like Inference and Forgetting.
His Equirectangular projection study combines topics in areas such as Depth map, Cube mapping, RANSAC and Distortion. His Benchmark research incorporates themes from Video tracking and Minimum bounding box. His research in Image intersects with topics in Object detection and Bounding overwatch.
Min Sun spends much of his time researching Artificial intelligence, Equirectangular projection, Computer vision, Depth map and Pixel. His study looks at the relationship between Artificial intelligence and fields such as Machine learning, as well as how they intersect with chemical problems. His work deals with themes such as Monocular, Feature, Face, Distortion and Cube mapping, which intersect with Depth map.
His research integrates issues of Image editing, Object, Translation, RGB color model and Pattern recognition in his study of Pixel. His Panorama research includes themes of Annotation, Robotics and Virtual reality, Human–computer interaction. Domain is integrated with Class, Object detection, Sight, Image and Bounding overwatch in his study.
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Make3D: Learning 3D Scene Structure from a Single Still Image
A. Saxena;Min Sun;A.Y. Ng.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)
Learning 3-D Scene Structure from a Single Still Image
A. Saxena;Min Sun;A.Y. Ng.
international conference on computer vision (2007)
A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss
Wan Ting Hsu;Chieh-Kai Lin;Ming-Ying Lee;Kerui Min.
meeting of the association for computational linguistics (2018)
No More Discrimination: Cross City Adaptation of Road Scene Segmenters
Yi-Hsin Chen;Wei-Yu Chen;Yu-Ting Chen;Bo-Cheng Tsai.
international conference on computer vision (2017)
Articulated part-based model for joint object detection and pose estimation
Min Sun;Silvio Savarese.
international conference on computer vision (2011)
Conditional regression forests for human pose estimation
Min Sun;Pushmeet Kohli;Jamie Shotton.
computer vision and pattern recognition (2012)
Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories
Hao Su;Min Sun;Li Fei-Fei;Silvio Savarese.
international conference on computer vision (2009)
A multi-view probabilistic model for 3D object classes
Min Sun;Hao Su;Silvio Savarese;Li Fei-Fei.
computer vision and pattern recognition (2009)
Depth-encoded hough voting for joint object detection and shape recovery
Min Sun;Gary Bradski;Bing-Xin Xu;Silvio Savarese.
european conference on computer vision (2010)
Ranking Domain-Specific Highlights by Analyzing Edited Videos
Min Sun;Ali Farhadi;Steven M. Seitz.
european conference on computer vision (2014)
Profile was last updated on December 6th, 2021.
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