Search Results for author:
Found 7 papers, 5 papers with code
ParaFormer: Parallel Attention Transformer for Efficient Feature Matching
Heavy computation is a bottleneck limiting deep-learningbased feature matching algorithms to be applied in many realtime applications.
PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points
Traditional temporal action detection (TAD) usually handles untrimmed videos with small number of action instances from a single label (e. g., ActivityNet, THUMOS).
Ranked #4 on
Temporal Action Localization
on MultiTHUMOS
DPNet: Dual-Path Network for Real-time Object Detection with Lightweight Attention
The recent advances of compressing high-accuracy convolution neural networks (CNNs) have witnessed remarkable progress for real-time object detection.
Ranked #13 on
Object Detection
on PASCAL VOC 2007
FPB: Feature Pyramid Branch for Person Re-Identification
In this paper, we propose a lightweight Feature Pyramid Branch (FPB) to extract features from different layers of networks and aggregate them in a bidirectional pyramid structure.
Ranked #6 on
Person Re-Identification
on CUHK03 labeled
TEA: Temporal Excitation and Aggregation for Action Recognition
Temporal modeling is key for action recognition in videos.
BiCANet: Bi-directional Contextual Aggregating Network for Image Semantic Segmentation
Exploring contextual information in convolution neural networks (CNNs) has gained substantial attention in recent years for semantic segmentation.
FDDWNet: A Lightweight Convolutional Neural Network for Real-time Sementic Segmentation
The comprehensive experiments demonstrate that our model achieves state-of-the-art results in terms of available speed and accuracy trade-off on CityScapes and CamVid datasets.
