Results 31 to 40 of about 61,033 (257)
Scene Attribute Semantic Relational Regularization for Transport-Travel Scene Understanding
IEEE Access, 2020 Attribute learning has improved the performance in scene understanding and scene recognition. However, there are many attributes described by words or short texts in a static scene and traffic crowd scene.
Xin Lei Wei +4 more
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From SLAM to Situational Awareness: Challenges and Survey
Sensors, 2023 The capability of a mobile robot to efficiently and safely perform complex missions is limited by its knowledge of the environment, namely the situation.
Hriday Bavle +4 more
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Artificial Intelligence, 2000 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chella, A., Frixione, M., Gaglio, S.
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Sketch-and-Fill Network for Semantic Segmentation
IEEE Access, 2021 Recent efforts in semantic segmentation using deep learning framework have made notable advances. While achieving high performance, however, they often require heavy computation, making them impractical to be used in real world applications.
Youngsaeng Jin +3 more
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Guest Editorial: Scene Understanding [PDF]
International Journal of Computer Vision, 2015 Scene understanding is the ability to visually analyze a scene to answer questions such as: What is happening? Why is it happening? What will happen next? What should I do? For example, in the context of driving safety, the vision system would need to recognize nearby people and vehicles, anticipate their motions, infer traffic patterns, and detect ...
Hoiem, Derek +3 more
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ISPRS International Journal of Geo-Information, 2021 Earth Observation data possess tremendous potential in understanding the dynamics of our planet. We propose the Semantics-driven Remote Sensing Scene Understanding (Sem-RSSU) framework for rendering comprehensive grounded spatio-contextual scene ...
Abhishek V. Potnis +2 more
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In-Place Scene Labelling and Understanding with Implicit Scene Representation [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Semantic labelling is highly correlated with geometry and radiance reconstruction, as scene entities with similar shape and appearance are more likely to come from similar classes. Recent implicit neural reconstruction techniques are appealing as they do not require prior training data, but the same fully self-supervised approach is not possible for ...
Shuaifeng Zhi +3 more
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Scene Understanding for Autonomous Driving
CoRR, 2021 To detect and segment objects in images based on their content is one of the most active topics in the field of computer vision. Nowadays, this problem can be addressed using Deep Learning architectures such as Faster R-CNN or YOLO, among others. In this paper, we study the behaviour of different configurations of RetinaNet, Faster R-CNN and Mask R-CNN
Òscar Lorente, Ian Riera, Aditya Rana
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Learning Direct Optimization for scene understanding [PDF]
Pattern Recognition, 2020 We develop a Learning Direct Optimization (LiDO) method for the refinement of a latent variable model that describes input image x. Our goal is to explain a single image x with an interpretable 3D computer graphics model having scene graph latent variables z (such as object appearance, camera position).
Romaszko, Lukasz +2 more
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Human's Scene Sketch Understanding [PDF]
Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval, 2016 Human's sketch understanding is important. It has many applications in human computer interaction, multimedia, and computer vision. Recognizing human sketches is also challenging. Previous methods focus on single-object sketch recognition. Understanding human's scene sketch that involves multiple objects and their complex interactions has not been ...
Yuxiang Ye, Yijuan Lu, Hao Jiang 0007
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