Search Results for author:
Found 9 papers, 2 papers with code
Spatio-Temporal Tuples Transformer for Skeleton-Based Action Recognition
And then a spatio-temporal tuples self-attention module is proposed to capture the relationship of different joints in consecutive frames.
FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection
We convert a lightweight FCOSR model to TensorRT format, which achieves 73. 93 mAP on DOTA1. 0 at a speed of 10. 68 FPS on Jetson Xavier NX with single scale.
More Separable and Easier to Segment: A Cluster Alignment Method for Cross-Domain Semantic Segmentation
Feature alignment between domains is one of the mainstream methods for Unsupervised Domain Adaptation (UDA) semantic segmentation.
GAFnet: Group Attention Fusion Network for PAN and MS Image High-Resolution Classification
Second, the group spatial attention and group spectral attention modules are proposed to extract image features.
New Generation Deep Learning For Video Object Dection:A Survery
Video object detection, a basic task in the computer vision field, is rapidly evolving and widely used.
Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification
Due to the limited amount and imbalanced classes of labeled training data, the conventional supervised learning can not ensure the discrimination of the learned feature for hyperspectral image (HSI) classification.
Discriminative Transformation Learning for Fuzzy Sparse Subspace Clustering
This paper develops a novel iterative framework for subspace clustering in a learned discriminative feature domain.
Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification
Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade.
Target Oriented High Resolution SAR Image Formation via Semantic Information Guided Regularizations
Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image.
