134 citations · 920 across the 72 of their papers we have counts for
18 papers · 1 filter
Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
Shu Zhang, Jincheng Xu, Yu-Chun Chen +4
Universal lesion detection from computed tomography (CT) slices is important for comprehensive disease screening. Since each lesion can locate in multiple adjacent slices, 3D conte…
Forecasting Irreversible Disease via Progression Learning
Botong Wu, Sijie Ren, Jing Li +3
Forecasting Parapapillary atrophy (PPA), i.e., a symptom related to most irreversible eye diseases, provides an alarm for implementing an intervention to slow down the disease prog…
An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation
Rongchang Xie, Chunyu Wang, Wenjun Zeng +1
Semi-supervised learning aims to boost the accuracy of a model by exploring unlabeled images. The state-of-the-art methods are consistency-based which learn about unlabeled images…
Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks
Jing Xu, Fangwei Zhong, Yizhou Wang
Maximum target coverage by adjusting the orientation of distributed sensors is an important problem in directional sensor networks (DSNs). This problem is challenging as the target…
Bilateral Asymmetry Guided Counterfactual Generating Network for Mammogram Classification
Chu-ran Wang, Jing Li, Fandong Zhang +4
Mammogram benign or malignant classification with only image-level labels is challenging due to the absence of lesion annotations. Motivated by the symmetric prior that the lesions…
Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field
Daochang Liu, Tingting Jiang, Yizhou Wang +3
Surgical skill assessment is important for surgery training and quality control. Prior works on this task largely focus on basic surgical tasks such as suturing and knot tying perf…
Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion
Daochang Liu, Yuhui Wei, Tingting Jiang +4
Surgical instrument segmentation is a key component in developing context-aware operating rooms. Existing works on this task heavily rely on the supervision of a large amount of la…
Assessing the Quality-of-Experience of Adaptive Bitrate Video Streaming
Zhengfang Duanmu, Wentao Liu, Zhuoran Li +4
The diversity of video delivery pipeline poses a grand challenge to the evaluation of adaptive bitrate (ABR) streaming algorithms and objective quality-of-experience (QoE) models.…
Leveraging both Lesion Features and Procedural Bias in Neuroimaging: An Dual-Task Split dynamics of inverse scale space
Xinwei Sun, Wenjing Han, Lingjing Hu +2
The prediction and selection of lesion features are two important tasks in voxel-based neuroimage analysis. Existing multivariate learning models take two tasks equivalently and op…
Augmented Bi-path Network for Few-shot Learning
Baoming Yan, Chen Zhou, Bo Zhao +5
Few-shot Learning (FSL) which aims to learn from few labeled training data is becoming a popular research topic, due to the expensive labeling cost in many real-world applications.…
TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning
Xinwei Sun, Yilun Xu, Peng Cao +4
Fusing data from multiple modalities provides more information to train machine learning systems. However, it is prohibitively expensive and time-consuming to label each modality w…
Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation
Shen Wang, Kongming Liang, Yiming Li +2
Brain midline delineation can facilitate the clinical evaluation of brain midline shift, which plays an important role in the diagnosis and prognosis of various brain pathology. Ne…
MetaFuse: A Pre-trained Fusion Model for Human Pose Estimation
Rongchang Xie, Chunyu Wang, Yizhou Wang
Cross view feature fusion is the key to address the occlusion problem in human pose estimation. The current fusion methods need to train a separate model for every pair of cameras…
Segmentation-based Method combined with Dynamic Programming for Brain Midline Delineation
Shen Wang, Kongming Liang, Chengwei Pan +5
The midline related pathological image features are crucial for evaluating the severity of brain compression caused by stroke or traumatic brain injury (TBI). The automated midline…
Self-Directed Online Machine Learning for Topology Optimization
Changyu Deng, Yizhou Wang, Can Qin +2
Topology optimization by optimally distributing materials in a given domain requires non-gradient optimizers to solve highly complicated problems. However, with hundreds of design…
A Generative Adversarial Network for AI-Aided Chair Design
Zhibo Liu, Feng Gao, Yizhou Wang
We present a method for improving human design of chairs. The goal of the method is generating enormous chair candidates in order to facilitate human designer by creating sketches…
Pose-Assisted Multi-Camera Collaboration for Active Object Tracking
Jing Li, Jing Xu, Fangwei Zhong +3
Active Object Tracking (AOT) is crucial to many visionbased applications, e.g., mobile robot, intelligent surveillance. However, there are a number of challenges when deploying act…
On Computation and Generalization of Generative Adversarial Imitation Learning
Minshuo Chen, Yizhou Wang, Tianyi Liu +4
Generative Adversarial Imitation Learning (GAIL) is a powerful and practical approach for learning sequential decision-making policies. Different from Reinforcement Learning (RL),…