Search Results for author:
Found 4 papers, 4 papers with code
Real-Time and Accurate Object Detection in Compressed Video by Long Short-term Feature Aggregation
Based on deep networks, video object detection is actively studied for pushing the limits of detection speed and accuracy.
RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation
To reciprocate these two tasks, we design a two-stream structure to learn features on both the object level (i. e., bounding boxes) and the pixel level (i. e., instance masks) jointly.
Ranked #94 on
Instance Segmentation
on COCO test-dev
Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation
Video object segmentation (VOS) aims at pixel-level object tracking given only the annotations in the first frame.
Ranked #1 on
Visual Object Tracking
on YouTube-VOS 2018
(Jaccard (Seen) metric)
Mask Scoring R-CNN
In this paper, we study this problem and propose Mask Scoring R-CNN which contains a network block to learn the quality of the predicted instance masks.
Ranked #74 on
Instance Segmentation
on COCO minival
