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Real-time 3D Traffic Cone Detection for Autonomous Driving
(2019)2019 IEEE Intelligent Vehicles Symposium (IV)Conference Paper -
Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understanding
(2018)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2018 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XIIIThis work addresses the problem of semantic scene understanding under dense fog. Although considerable progress has been made in semantic scene understanding, it is mainly related to clear-weather scenes. Extending recognition methods to adverse weather conditions such as fog is crucial for outdoor applications. In this paper, we propose a novel method, named Curriculum Model Adaptation (CMAda), which gradually adapts a semantic segmentation ...Conference Paper -
End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners
(2018)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2018Conference Paper -
Example-based Facade Texture Synthesis
(2013)2013 IEEE International Conference on Computer Vision (ICCV 2013)Conference Paper -
Latent Dictionary Learning for Sparse Representation based Classification
(2014)Proceedings. 2014 IEEE Conference on Computer Vision and Pattern Recognition CVPR 2014Conference Paper -
Weakly Supervised 3D Object Detection from Lidar Point Cloud
(2020)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2020It is laborious to manually label point cloud data for training high-quality 3D object detectors. This work proposes a weakly supervised approach for 3D object detection, only requiring a small set of weakly annotated scenes, associated with a few precisely labeled object instances. This is achieved by a two-stage architecture design. Stage-1 learns to generate cylindrical object proposals under weak supervision, i.e., only the horizontal ...Conference Paper -
Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime
(2018)2018 21st International Conference on Intelligent Transportation Systems (ITSC)This work addresses the problem of semantic image segmentation of nighttime scenes. Although considerable progress has been made in semantic image segmentation, it is mainly related to daytime scenarios. This paper proposes a novel method to progressive adapt the semantic models trained on daytime scenes, along with large-scale annotations therein, to nighttime scenes via the bridge of twilight time - the time between dawn and sunrise, ...Conference Paper -
Object Referring in Videos with Language and Human Gaze
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionConference Paper -
Object Referring in Visual Scene with Spoken Language
(2018)2018 IEEE Winter Conference on Applications of Computer Vision (WACV)Conference Paper -
Scale-Aware Alignment of Hierarchical Image Segmentation
(2016)Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern RecognitionConference Paper