790 citations · 1.6k across the 16 of their papers we have counts for
16 papers
LatentMove: Towards Complex Human Movement Video Generation
Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +5
Image-to-video (I2V) generation seeks to produce realistic motion sequences from a single reference image. Although recent methods exhibit strong temporal consistency, they often s…
Watch and Listen: Understanding Audio-Visual-Speech Moments with Multimodal LLM
Zinuo Li, Xian Zhang, Yongxin Guo +5
Humans naturally understand moments in a video by integrating visual and auditory cues. For example, localizing a scene in the video like "A scientist passionately speaks on wildli…
Amodal Intra-class Instance Segmentation: Synthetic Datasets and Benchmark
Jiayang Ao, Qiuhong Ke, Krista A. Ehinger
Images of realistic scenes often contain intra-class objects that are heavily occluded from each other, making the amodal perception task that requires parsing the occluded parts o…
Image Amodal Completion: A Survey
Jiayang Ao, Qiuhong Ke, Krista A. Ehinger
Existing computer vision systems can compete with humans in understanding the visible parts of objects, but still fall far short of humans when it comes to depicting the invisible…
Iterative Geometry-Aware Cross Guidance Network for Stereo Image Inpainting
Ang Li, Shanshan Zhao, Qingjie Zhang +1
Currently, single image inpainting has achieved promising results based on deep convolutional neural networks. However, inpainting on stereo images with missing regions has not bee…
Video Joint Modelling Based on Hierarchical Transformer for Co-summarization
Li Haopeng, Ke Qiuhong, Gong Mingming +1
Video summarization aims to automatically generate a summary (storyboard or video skim) of a video, which can facilitate large-scale video retrieval and browsing. Most of the exist…
Spatial-Temporal Transformer for 3D Point Cloud Sequences
Yimin Wei, Hao Liu, Tingting Xie +2
Effective learning of spatial-temporal information within a point cloud sequence is highly important for many down-stream tasks such as 4D semantic segmentation and 3D action recog…
The Multi-Modal Video Reasoning and Analyzing Competition
Haoran Peng, He Huang, Li Xu +15
In this paper, we introduce the Multi-Modal Video Reasoning and Analyzing Competition (MMVRAC) workshop in conjunction with ICCV 2021. This competition is composed of four differen…
Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting
Ang Li, Qiuhong Ke, Xingjun Ma +4
Deep image inpainting aims to restore damaged or missing regions in an image with realistic contents. While having a wide range of applications such as object removal and image rec…
HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks
Yunxiang Zhao, Qiuhong Ke, Flip Korn +2
Hexagonal CNN models have shown superior performance in applications such as IACT data analysis and aerial scene classification due to their better rotation symmetry and reduced an…
Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions
Nodens Koren, Qiuhong Ke, Yisen Wang +2
Understanding the actions of both humans and artificial intelligence (AI) agents is important before modern AI systems can be fully integrated into our daily life. In this paper, w…
Human Action Recognition from Various Data Modalities: A Review
Zehua Sun, Qiuhong Ke, Hossein Rahmani +3
Human Action Recognition (HAR) aims to understand human behavior and assign a label to each action. It has a wide range of applications, and therefore has been attracting increasin…
Hierarchical Paired Channel Fusion Network for Street Scene Change Detection
Yinjie Lei, Duo Peng, Pingping Zhang +2
Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging ta…
Long-Term Anticipation of Activities with Cycle Consistency
Yazan Abu Farha, Qiuhong Ke, Bernt Schiele +1
With the success of deep learning methods in analyzing activities in videos, more attention has recently been focused towards anticipating future activities. However, most of the w…
A New Representation of Skeleton Sequences for 3D Action Recognition
Qiuhong Ke, Mohammed Bennamoun, Senjian An +2
This paper presents a new method for 3D action recognition with skeleton sequences (i.e., 3D trajectories of human skeleton joints). The proposed method first transforms each skele…
Leveraging Structural Context Models and Ranking Score Fusion for Human Interaction Prediction
Qiuhong Ke, Mohammed Bennamoun, Senjian An +2
Predicting an interaction before it is fully executed is very important in applications such as human-robot interaction and video surveillance. In a two-human interaction scenario,…