Search Results for author:
Found 6 papers, 1 papers with code
Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition
Fine-grained action recognition is a challenging task in computer vision.
A Multi-task Framework for Infrared Small Target Detection and Segmentation
First, with the use of UNet as the backbone to maintain resolution and semantic information, our model can achieve a higher detection accuracy than other state-of-the-art methods by attaching a simple anchor-free head.
TAILOR: Teaching with Active and Incremental Learning for Object Registration
When deploying a robot to a new task, one often has to train it to detect novel objects, which is time-consuming and labor-intensive.
Joint Learning On The Hierarchy Representation for Fine-Grained Human Action Recognition
Inspired by the recently proposed hierarchy representation of fine-grained actions in FineGym and SlowFast network for action recognition, we propose a novel multi-task network which exploits the FineGym hierarchy representation to achieve effective joint learning and prediction for fine-grained human action recognition.
Electrical excitation and manipulation of spin-waves in spin Hall Nano-Oscillators
While in the nanogap SHNOs with strong perpendicular magnetic anisotropy (PMA), besides both nonlinear bullet soliton and propagating spin-wave mode are achieved and controlled by varying the external magnetic field and current, the magnetic bubble skyrmion mode also can be excited at a low in-plane magnetic field.
Mesoscale and Nanoscale Physics Materials Science
6D Pose Estimation with Correlation Fusion
To our best knowledge, this is the first work to explore effective intra- and inter-modality fusion in 6D pose estimation.
