Vision-based drone-view object detection suffers from severe performance degradation
under adverse conditions (eg, foggy weather, poor illumination). To remedy this, leveraging …

Despite the remarkable progress facilitated by learning-based stereo-matching algorithms,
the performance in the ill-conditioned regions, such as the occluded regions, remains a …

Geospatial object detection is an essential task in remote sensing community. One-stage
methods based on deep learning have faster running speed but cannot reach higher …

Object detection with camera has achieved promising results using deep learning methods,
but it suffers degraded performance under adverse conditions (eg, foggy weather, poor …

Region proposal is crucial for the two-stage object detectors. Recently, the RGB-based
region proposal approaches have achieved impressive progress. However, they still suffer …

Despite the remarkable progress facilitated by learning-based stereo matching algorithms,
disparity estimation in low-texture, occluded, and bordered regions still remain bottlenecks …

Existing single-view bird 3D reconstruction methods mostly cannot well recover the local
geometry such as feet and wing tips, and the resulting 3D models often appear to have poor …