… of object detection, affinity computation and data association in real time. This paper presents
an efficient multi-modal MOT framework with online joint detection … for joint object detection …

… camera and LiDAR is achieved over two object detection stages. In the first stage, we aim
to generate the strong joint camera… The auto-calibrated feature projection maps the camera-…

… a radar-camera fusion algorithm for joint object detection and distance … object detection
network that fuses radar point clouds and learned image features to generate accurate object …

… joint object detection and tracking (JoDT) framework for 3D object detection and tracking
based on camera … The proposed method, referred to as 3D DetecTrack, enables the detector …

… In object detection, both accuracy and running speed are critical considerations. YOLO and
… design a joint learning network for camera relocalization and object detection by combining …

… camera–LiDAR sequential fusion 3D object detection pipeline have been enriched to make
it more suitable for its use in multi-camera … of the same object appear. To this end, the 2D …

… performance of object detection especially at long range and for small objects. Thus, in
this work, we focus on fusing camera images with a state-of-the-art LiDAR based detector [18]. …

… We illustrate this in more details with three mainstream camera-based methods: (1) Monocular
3D object detection methods, eg CenterNet [10] and FCOS3D [7], predict 3D bounding …

… This paper proposes a novel joint learning and denselycooperative fusion (JL-DCF) architecture
for RGB-D salient object detection. Existing models … As depth cameras such as Kinect …

… the object relative to the camera. Object detection systems construct a model for an object
class … Models that additionally predict human joint locations, in addition to bounding boxes and …