Search Results for author:
Found 10 papers, 5 papers with code
SR-GNN: Spatial Relation-aware Graph Neural Network for Fine-Grained Image Categorization
Over the past few years, a significant progress has been made in deep convolutional neural networks (CNNs)-based image recognition.
Ranked #1 on
Fine-Grained Image Classification
on Stanford Dogs
Fine-Grained Image Classification
Human-Object Interaction Detection
+3
Retinal Structure Detection in OCTA Image via Voting-based Multi-task Learning
Automated detection of retinal structures, such as retinal vessels (RV), the foveal avascular zone (FAZ), and retinal vascular junctions (RVJ), are of great importance for understanding diseases of the eye and clinical decision-making.
Benchmarking Deep Reinforcement Learning Algorithms for Vision-based Robotics
To the best of our knowledge, such a benchmarking study is not available for the above two vision-based robotics problems making it a novel contribution in the field.
Attend and Guide (AG-Net): A Keypoints-driven Attention-based Deep Network for Image Recognition
We address this by proposing an end-to-end CNN model, which learns meaningful features linking fine-grained changes using our novel attention mechanism.
Ranked #1 on
Image Classification
on Caltech-256
An attention-driven hierarchical multi-scale representation for visual recognition
Convolutional Neural Networks (CNNs) have revolutionized the understanding of visual content.
Coarse Temporal Attention Network (CTA-Net) for Driver's Activity Recognition
Our model is named Coarse Temporal Attention Network (CTA-Net), in which coarse temporal branches are introduced in a trainable glimpse network.
Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification
We evaluate our approach using six state-of-the-art (SotA) backbone networks and eight benchmark datasets.
Ranked #1 on
Fine-Grained Image Classification
on Food-101
Regional Attention Network (RAN) for Head Pose and Fine-grained Gesture Recognition
Affect is often expressed via non-verbal body language such as actions/gestures, which are vital indicators for human behaviors.
Facial Expression Recognition
Facial Expression Recognition (FER)
+2
Unsupervised Monocular Depth Estimation for Night-time Images using Adversarial Domain Feature Adaptation
We propose to solve this problem by posing it as a domain adaptation problem where a network trained with day-time images is adapted to work for night-time images.
Orderly Disorder in Point Cloud Domain
Our method extracts the deep patterns inside a 3D object via creating a dynamic link to seek the most stable patterns and at once, throws away the unstable ones.
