29 citations · 111 across the 23 of their papers we have counts for
15 papers · 1 filter
X-ray Insights Unleashed: Pioneering the Enhancement of Multi-Label Long-Tail Data
Xinquan Yang, Jinheng Xie, Yawen Huang +6
Long-tailed pulmonary anomalies in chest radiography present formidable diagnostic challenges. Despite the recent strides in diffusion-based methods for enhancing the representatio…
Robust Source-Free Domain Adaptation for Medical Image Segmentation based on Curriculum Learning
Ziqi Zhang, Yuexiang Li, Yawen Huang +6
Recent studies have uncovered a new research line, namely source-free domain adaptation, which adapts a model to target domains without using the source data. Such a setting can ad…
TRACE: Temporally Reliable Anatomically-Conditioned 3D CT Generation with Enhanced Efficiency
Minye Shao, Xingyu Miao, Haoran Duan +7
3D medical image generation is essential for data augmentation and patient privacy, calling for reliable and efficient models suited for clinical practice. However, current methods…
URoadNet: Dual Sparse Attentive U-Net for Multiscale Road Network Extraction
Jie Song, Yue Sun, Ziyun Cai +3
The challenges of road network segmentation demand an algorithm capable of adapting to the sparse and irregular shapes, as well as the diverse context, which often leads traditiona…
Wearable-based behaviour interpolation for semi-supervised human activity recognition
Haoran Duan, Shidong Wang, Varun Ojha +5
While traditional feature engineering for Human Activity Recognition (HAR) involves a trial-anderror process, deep learning has emerged as a preferred method for high-level represe…
AnomalyXFusion: Multi-modal Anomaly Synthesis with Diffusion
Jie Hu, Yawen Huang, Yilin Lu +4
Anomaly synthesis is one of the effective methods to augment abnormal samples for training. However, current anomaly synthesis methods predominantly rely on texture information as…
Learning Long-form Video Prior via Generative Pre-Training
Jinheng Xie, Jiajun Feng, Zhaoxu Tian +8
Concepts involved in long-form videos such as people, objects, and their interactions, can be viewed as following an implicit prior. They are notably complex and continue to pose c…
NeRF2Points: Large-Scale Point Cloud Generation From Street Views' Radiance Field Optimization
Peng Tu, Xun Zhou, Mingming Wang +7
Neural Radiance Fields (NeRF) have emerged as a paradigm-shifting methodology for the photorealistic rendering of objects and environments, enabling the synthesis of novel viewpoin…
ConRF: Zero-shot Stylization of 3D Scenes with Conditioned Radiation Fields
Xingyu Miao, Yang Bai, Haoran Duan +4
Most of the existing works on arbitrary 3D NeRF style transfer required retraining on each single style condition. This work aims to achieve zero-shot controlled stylization in 3D…
CTNeRF: Cross-Time Transformer for Dynamic Neural Radiance Field from Monocular Video
Xingyu Miao, Yang Bai, Haoran Duan +4
The goal of our work is to generate high-quality novel views from monocular videos of complex and dynamic scenes. Prior methods, such as DynamicNeRF, have shown impressive performa…
DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost Volume
Xingyu Miao, Yang Bai, Haoran Duan +5
Self-supervised monocular depth estimation methods typically rely on the reprojection error to capture geometric relationships between successive frames in static environments. How…
A New Perspective to Boost Vision Transformer for Medical Image Classification
Yuexiang Li, Yawen Huang, Nanjun He +2
Transformer has achieved impressive successes for various computer vision tasks. However, most of existing studies require to pretrain the Transformer backbone on a large-scale lab…
FemtoDet: An Object Detection Baseline for Energy Versus Performance Tradeoffs
Peng Tu, Xu Xie, Guo AI +3
Efficient detectors for edge devices are often optimized for parameters or speed count metrics, which remain in weak correlation with the energy of detectors. However, some vision…
A Benchmark for Weakly Semi-Supervised Abnormality Localization in Chest X-Rays
Haoqin Ji, Haozhe Liu, Yuexiang Li +7
Accurate abnormality localization in chest X-rays (CXR) can benefit the clinical diagnosis of various thoracic diseases. However, the lesion-level annotation can only be performed…
Robust Representation via Dynamic Feature Aggregation
Haozhe Liu, Haoqin Ji, Yuexiang Li +5
Deep convolutional neural network (CNN) based models are vulnerable to the adversarial attacks. One of the possible reasons is that the embedding space of CNN based model is sparse…