7.1k citations · 8.9k across the 43 of their papers we have counts for
19 papers · 1 filter
Micro-Expression Recognition via Fine-Grained Dynamic Perception
Zhiwen Shao, Yifan Cheng, Fan Zhang +4
Facial micro-expression recognition (MER) is a challenging task, due to the transience, subtlety, and dynamics of micro-expressions (MEs). Most existing methods resort to hand-craf…
G-VEval: A Versatile Metric for Evaluating Image and Video Captions Using GPT-4o
Tony Cheng Tong, Sirui He, Zhiwen Shao +1
Evaluation metric of visual captioning is important yet not thoroughly explored. Traditional metrics like BLEU, METEOR, CIDEr, and ROUGE often miss semantic depth, while trained me…
CurvNet: Latent Contour Representation and Iterative Data Engine for Curvature Angle Estimation
Zhiwen Shao, Yichen Yuan, Lizhuang Ma +1
Curvature angle is a quantitative measurement of a curve, in which Cobb angle is customized for spinal curvature. Automatic Cobb angle measurement from X-ray images is crucial for…
MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving
Kai Chen, Lanqing Hong, Hang Xu +2
Autonomous driving has attracted much attention over the years but turns out to be harder than expected, probably due to the difficulty of labeled data collection for model trainin…
Stereo Waterdrop Removal with Row-wise Dilated Attention
Zifan Shi, Na Fan, Dit-Yan Yeung +1
Existing vision systems for autonomous driving or robots are sensitive to waterdrops adhered to windows or camera lenses. Most recent waterdrop removal approaches take a single ima…
Marginalized Average Attentional Network for Weakly-Supervised Learning
Yuan Yuan, Yueming Lyu, Xi Shen +2
In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the overestimation of the most sali…
Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues
Ting Sun, Lei Tai, Zhihan Gao +2
This paper proposes a novel weakly-supervised semantic segmentation method using image-level label only. The class-specific activation maps from the well-trained classifiers are us…
Coupled Recurrent Network (CRN)
Lin Sun, Kui Jia, Yuejia Shen +3
Many semantic video analysis tasks can benefit from multiple, heterogenous signals. For example, in addition to the original RGB input sequences, sequences of optical flow are usua…
Semi-Semantic Line-Cluster Assisted Monocular SLAM for Indoor Environments
Ting Sun, Dezhen Song, Dit-Yan Yeung +1
This paper presents a novel method to reduce the scale drift for indoor monocular simultaneous localization and mapping (SLAM). We leverage the prior knowledge that in the indoor e…
Point-cloud-based place recognition using CNN feature extraction
Ting Sun, Ming Liu, Haoyang Ye +1
This paper proposes a novel point-cloud-based place recognition system that adopts a deep learning approach for feature extraction. By using a convolutional neural network pre-trai…
Lattice Long Short-Term Memory for Human Action Recognition
Lin Sun, Kui Jia, Kevin Chen +3
Human actions captured in video sequences are three-dimensional signals characterizing visual appearance and motion dynamics. To learn action patterns, existing methods adopt Convo…
Temporal Dynamic Graph LSTM for Action-driven Video Object Detection
Yuan Yuan, Xiaodan Liang, Xiaolong Wang +2
In this paper, we investigate a weakly-supervised object detection framework. Most existing frameworks focus on using static images to learn object detectors. However, these detect…
Spatiotemporal Modeling for Crowd Counting in Videos
Feng Xiong, Xingjian Shi, Dit-Yan Yeung
Region of Interest (ROI) crowd counting can be formulated as a regression problem of learning a mapping from an image or a video frame to a crowd density map. Recently, convolution…
Fine-Grained Categorization via CNN-Based Automatic Extraction and Integration of Object-Level and Part-Level Features
Ting Sun, Lin Sun, Dit-Yan Yeung
Fine-grained categorization can benefit from part-based features which reveal subtle visual differences between object categories. Handcrafted features have been widely used for pa…
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
Xingjian Shi, Zhihan Gao, Leonard Lausen +4
With the goal of making high-resolution forecasts of regional rainfall, precipitation nowcasting has become an important and fundamental technology underlying various public servic…
ZM-Net: Real-time Zero-shot Image Manipulation Network
Hao Wang, Xiaodan Liang, Hao Zhang +2
Many problems in image processing and computer vision (e.g. colorization, style transfer) can be posed as 'manipulating' an input image into a corresponding output image given a us…
Human Action Recognition using Factorized Spatio-Temporal Convolutional Networks
Lin Sun, Kui Jia, Dit-Yan Yeung +1
Human actions in video sequences are three-dimensional (3D) spatio-temporal signals characterizing both the visual appearance and motion dynamics of the involved humans and objects…
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian Shi, Zhourong Chen, Hao Wang +3
The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time. Very few previous studies have examined t…
Understanding and Diagnosing Visual Tracking Systems
Naiyan Wang, Jianping Shi, Dit-Yan Yeung +1
Several benchmark datasets for visual tracking research have been proposed in recent years. Despite their usefulness, whether they are sufficient for understanding and diagnosing t…