40 citations · 242 across the 31 of their papers we have counts for
31 papers · 1 filter
Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +4
Recently, large-scale pre-trained language-image models like CLIP have shown extraordinary capabilities for understanding spatial contents, but naively transferring such models to…
Towards Real-World Visual Tracking with Temporal Contexts
Ziang Cao, Ziyuan Huang, Liang Pan +3
Visual tracking has made significant improvements in the past few decades. Most existing state-of-the-art trackers 1) merely aim for performance in ideal conditions while overlooki…
Temporally-Adaptive Models for Efficient Video Understanding
Ziyuan Huang, Shiwei Zhang, Liang Pan +4
Spatial convolutions are extensively used in numerous deep video models. It fundamentally assumes spatio-temporal invariance, i.e., using shared weights for every location in diffe…
Rethinking Efficient Tuning Methods from a Unified Perspective
Zeyinzi Jiang, Chaojie Mao, Ziyuan Huang +3
Parameter-efficient transfer learning (PETL) based on large-scale pre-trained foundation models has achieved great success in various downstream applications. Existing tuning metho…
Physically Plausible Animation of Human Upper Body from a Single Image
Ziyuan Huang, Zhengping Zhou, Yung-Yu Chuang +2
We present a new method for generating controllable, dynamically responsive, and photorealistic human animations. Given an image of a person, our system allows the user to generate…
Progressive Learning without Forgetting
Tao Feng, Hangjie Yuan, Mang Wang +3
Learning from changing tasks and sequential experience without forgetting the obtained knowledge is a challenging problem for artificial neural networks. In this work, we focus on…
PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework
Bowen Li, Ziyuan Huang, Junjie Ye +4
Visual object tracking is essential to intelligent robots. Most existing approaches have ignored the online latency that can cause severe performance degradation during real-world…
RLIP: Relational Language-Image Pre-training for Human-Object Interaction Detection
Hangjie Yuan, Jianwen Jiang, Samuel Albanie +4
The task of Human-Object Interaction (HOI) detection targets fine-grained visual parsing of humans interacting with their environment, enabling a broad range of applications. Prior…
MAR: Masked Autoencoders for Efficient Action Recognition
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +5
Standard approaches for video recognition usually operate on the full input videos, which is inefficient due to the widely present spatio-temporal redundancy in videos. Recent prog…
Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +6
Natural videos provide rich visual contents for self-supervised learning. Yet most existing approaches for learning spatio-temporal representations rely on manually trimmed videos,…
TCTrack: Temporal Contexts for Aerial Tracking
Ziang Cao, Ziyuan Huang, Liang Pan +3
Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers. In this work, we present TCTrack, a comprehensive framework to fully explo…
TAda! Temporally-Adaptive Convolutions for Video Understanding
Ziyuan Huang, Shiwei Zhang, Liang Pan +4
Spatial convolutions are widely used in numerous deep video models. It fundamentally assumes spatio-temporal invariance, i.e., using shared weights for every location in different…
Support-Set Based Cross-Supervision for Video Grounding
Xinpeng Ding, Nannan Wang, Shiwei Zhang +5
Current approaches for video grounding propose kinds of complex architectures to capture the video-text relations, and have achieved impressive improvements. However, it is hard to…
ParamCrop: Parametric Cubic Cropping for Video Contrastive Learning
Zhiwu Qing, Ziyuan Huang, Shiwei Zhang +5
The central idea of contrastive learning is to discriminate between different instances and force different views from the same instance to share the same representation. To avoid…
Exploring Stronger Feature for Temporal Action Localization
Zhiwu Qing, Xiang Wang, Ziyuan Huang +6
Temporal action localization aims to localize starting and ending time with action category. Limited by GPU memory, mainstream methods pre-extract features for each video. Therefor…
Proposal Relation Network for Temporal Action Detection
Xiang Wang, Zhiwu Qing, Ziyuan Huang +6
This technical report presents our solution for temporal action detection task in AcitivityNet Challenge 2021. The purpose of this task is to locate and identify actions of interes…
Weakly-Supervised Temporal Action Localization Through Local-Global Background Modeling
Xiang Wang, Zhiwu Qing, Ziyuan Huang +6
Weakly-Supervised Temporal Action Localization (WS-TAL) task aims to recognize and localize temporal starts and ends of action instances in an untrimmed video with only video-level…
Relation Modeling in Spatio-Temporal Action Localization
Yutong Feng, Jianwen Jiang, Ziyuan Huang +5
This paper presents our solution to the AVA-Kinetics Crossover Challenge of ActivityNet workshop at CVPR 2021. Our solution utilizes multiple types of relation modeling methods for…
A Stronger Baseline for Ego-Centric Action Detection
Zhiwu Qing, Ziyuan Huang, Xiang Wang +7
This technical report analyzes an egocentric video action detection method we used in the 2021 EPIC-KITCHENS-100 competition hosted in CVPR2021 Workshop. The goal of our task is to…
Towards Training Stronger Video Vision Transformers for EPIC-KITCHENS-100 Action Recognition
Ziyuan Huang, Zhiwu Qing, Xiang Wang +7
With the recent surge in the research of vision transformers, they have demonstrated remarkable potential for various challenging computer vision applications, such as image recogn…
Multi-Scale Feature Aggregation by Cross-Scale Pixel-to-Region Relation Operation for Semantic Segmentation
Yechao Bai, Ziyuan Huang, Lyuyu Shen +3
Exploiting multi-scale features has shown great potential in tackling semantic segmentation problems. The aggregation is commonly done with sum or concatenation (concat) followed b…
Self-supervised Motion Learning from Static Images
Ziyuan Huang, Shiwei Zhang, Jianwen Jiang +3
Motions are reflected in videos as the movement of pixels, and actions are essentially patterns of inconsistent motions between the foreground and the background. To well distingui…
Towards Accurate Human Pose Estimation in Videos of Crowded Scenes
Li Yuan, Shuning Chang, Xuecheng Nie +5
Video-based human pose estimation in crowded scenes is a challenging problem due to occlusion, motion blur, scale variation and viewpoint change, etc. Prior approaches always fail…
A Simple Baseline for Pose Tracking in Videos of Crowded Scenes
Li Yuan, Shuning Chang, Ziyuan Huang +6
This paper presents our solution to ACM MM challenge: Large-scale Human-centric Video Analysis in Complex Events\cite{lin2020human}; specifically, here we focus on Track3: Crowd Po…