Search Results for author:
Found 11 papers, 6 papers with code
Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases
Large Vision-Language Models (LVLMs), due to the remarkable visual reasoning ability to understand images and videos, have received widespread attention in the autonomous driving domain, which significantly advances the development of interpretable end-to-end autonomous driving.
Knowledge Augmented Relation Inference for Group Activity Recognition
Specifically, the framework consists of a Visual Representation Module to extract individual appearance features, a Knowledge Augmented Semantic Relation Module explore semantic representations of individual actions, and a Knowledge-Semantic-Visual Interaction Module aims to integrate visual and semantic information by the knowledge.
Weakly Supervised Learning of Keypoints for 6D Object Pose Estimation
Specifically, we assign a set of arbitrarily chosen 3D keypoints to represent each unknown target 3D object and learn a network to detect their 2D projections that comply with the relative camera viewpoints.
Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion Perception
The inaccessibility of reference videos with pristine quality and the complexity of authentic distortions pose great challenges for this kind of blind video quality assessment (BVQA) task.
Ranked #4 on
Video Quality Assessment
on MSU NR VQA Database
DeepOpht: Medical Report Generation for Retinal Images via Deep Models and Visual Explanation
To train and validate the effectiveness of our DNN-based module, we propose a large-scale retinal disease image dataset.
Shape Prior Deformation for Categorical 6D Object Pose and Size Estimation
We present a novel learning approach to recover the 6D poses and sizes of unseen object instances from an RGB-D image.
Robust 6D Object Pose Estimation by Learning RGB-D Features
Accurate 6D object pose estimation is fundamental to robotic manipulation and grasping.
Synthesizing New Retinal Symptom Images by Multiple Generative Models
Age-Related Macular Degeneration (AMD) is an asymptomatic retinal disease which may result in loss of vision.
Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model
Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists.
Ambient Hidden Space of Generative Adversarial Networks
In this paper, we extend the ambient module to the hidden space of the generator, and provide the uniqueness condition and the corresponding strategy for the ambient hidden generator in the adversarial training process.
Towards Adversarial Training with Moderate Performance Improvement for Neural Network Classification
It has been demonstrated that deep neural networks are prone to noisy examples particular adversarial samples during inference process.
