Search Results for author:
Found 5 papers, 2 papers with code
CM-PIE: Cross-modal perception for interactive-enhanced audio-visual video parsing
Audio-visual video parsing is the task of categorizing a video at the segment level with weak labels, and predicting them as audible or visible events.
Multi-Frequency Representation Enhancement with Privilege Information for Video Super-Resolution
CNN's limited receptive field restricts its ability to capture long-range spatial-temporal dependencies, leading to unsatisfactory performance in video super-resolution.
A Survey of Fish Tracking Techniques Based on Computer Vision
Fish tracking is a key technology for obtaining movement trajectories and identifying abnormal behavior.
SOTR: Segmenting Objects with Transformers
Most recent transformer-based models show impressive performance on vision tasks, even better than Convolution Neural Networks (CNN).
LeafMask: Towards Greater Accuracy on Leaf Segmentation
In this work, we present the LeafMask neural network, a new end-to-end model to delineate each leaf region and count the number of leaves, with two main components: 1) the mask assembly module merging position-sensitive bases of each predicted box after non-maximum suppression (NMS) and corresponding coefficients to generate original masks; 2) the mask refining module elaborating leaf boundaries from the mask assembly module by the point selection strategy and predictor.
Ranked #1 on
Instance Segmentation
on Leaf Segmentation Challenge
