Search Results for author: Shiwei Zhang

Found 25 papers, 11 papers with code

Hybrid Relation Guided Set Matching for Few-shot Action Recognition

no code implementations28 Apr 2022 Xiang Wang, Shiwei Zhang, Zhiwu Qing, Mingqian Tang, Zhengrong Zuo, Changxin Gao, Rong Jin, Nong Sang

To overcome the two limitations, we propose a novel Hybrid Relation guided Set Matching (HyRSM) approach that incorporates two key components: hybrid relation module and set matching metric.

Few Shot Action Recognition set matching

TCTrack: Temporal Contexts for Aerial Tracking

1 code implementation3 Mar 2022 Ziang Cao, Ziyuan Huang, Liang Pan, Shiwei Zhang, Ziwei Liu, Changhong Fu

Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers.

Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection

no code implementations18 Oct 2021 Shiwei Zhang, Wei Ke, Lin Yang

Weakly supervised object detection (WSOD) is a challenging task that requires simultaneously learn object classifiers and estimate object locations under the supervision of image category labels.

Multiple Instance Learning Weakly Supervised Object Detection

TAda! Temporally-Adaptive Convolutions for Video Understanding

2 code implementations ICLR 2022 Ziyuan Huang, Shiwei Zhang, Liang Pan, Zhiwu Qing, Mingqian Tang, Ziwei Liu, Marcelo H. Ang Jr

This work presents Temporally-Adaptive Convolutions (TAdaConv) for video understanding, which shows that adaptive weight calibration along the temporal dimension is an efficient way to facilitate modelling complex temporal dynamics in videos.

Ranked #31 on Action Recognition on Something-Something V2 (using extra training data)

Action Classification Action Recognition +2

ParamCrop: Parametric Cubic Cropping for Video Contrastive Learning

1 code implementation24 Aug 2021 Zhiwu Qing, Ziyuan Huang, Shiwei Zhang, Mingqian Tang, Changxin Gao, Marcelo H. Ang Jr, Rong Jin, Nong Sang

The visualizations show that ParamCrop adaptively controls the center distance and the IoU between two augmented views, and the learned change in the disparity along the training process is beneficial to learning a strong representation.

Contrastive Learning

Support-Set Based Cross-Supervision for Video Grounding

no code implementations ICCV 2021 Xinpeng Ding, Nannan Wang, Shiwei Zhang, De Cheng, Xiaomeng Li, Ziyuan Huang, Mingqian Tang, Xinbo Gao

The contrastive objective aims to learn effective representations by contrastive learning, while the caption objective can train a powerful video encoder supervised by texts.

Contrastive Learning

OadTR: Online Action Detection with Transformers

1 code implementation ICCV 2021 Xiang Wang, Shiwei Zhang, Zhiwu Qing, Yuanjie Shao, Zhengrong Zuo, Changxin Gao, Nong Sang

Most recent approaches for online action detection tend to apply Recurrent Neural Network (RNN) to capture long-range temporal structure.

Action Detection

A Stronger Baseline for Ego-Centric Action Detection

1 code implementation13 Jun 2021 Zhiwu Qing, Ziyuan Huang, Xiang Wang, Yutong Feng, Shiwei Zhang, Jianwen Jiang, Mingqian Tang, Changxin Gao, Marcelo H. Ang Jr, Nong Sang

This technical report analyzes an egocentric video action detection method we used in the 2021 EPIC-KITCHENS-100 competition hosted in CVPR2021 Workshop.

Action Detection

Self-supervised Motion Learning from Static Images

1 code implementation CVPR 2021 Ziyuan Huang, Shiwei Zhang, Jianwen Jiang, Mingqian Tang, Rong Jin, Marcelo Ang

We furthermore introduce a static mask in pseudo motions to create local motion patterns, which forces the model to additionally locate notable motion areas for the correct classification. We demonstrate that MoSI can discover regions with large motion even without fine-tuning on the downstream datasets.

Action Recognition Self-Supervised Learning

Self-Supervised Video Representation Learning with Constrained Spatiotemporal Jigsaw

no code implementations1 Jan 2021 Yuqi Huo, Mingyu Ding, Haoyu Lu, Zhiwu Lu, Tao Xiang, Ji-Rong Wen, Ziyuan Huang, Jianwen Jiang, Shiwei Zhang, Mingqian Tang, Songfang Huang, Ping Luo

With the constrained jigsaw puzzles, instead of solving them directly, which could still be extremely hard, we carefully design four surrogate tasks that are more solvable but meanwhile still ensure that the learned representation is sensitive to spatiotemporal continuity at both the local and global levels.

Representation Learning

Tuning the quantumness of simple Bose systems: A universal phase diagram

no code implementations9 Aug 2020 Youssef Kora, Massimo Boninsegni, Dam Thanh Son, Shiwei Zhang

We present a comprehensive theoretical study of the phase diagram of a system of many Bose particles interacting with a two-body central potential of the so-called Lennard-Jones form.

Statistical Mechanics

Multi-Level Temporal Pyramid Network for Action Detection

no code implementations7 Aug 2020 Xiang Wang, Changxin Gao, Shiwei Zhang, Nong Sang

By this means, the proposed MLTPN can learn rich and discriminative features for different action instances with different durations.

14 Action Detection

Less is More: Rejecting Unreliable Reviews for Product Question Answering

1 code implementation9 Jul 2020 Shiwei Zhang, Xiuzhen Zhang, Jey Han Lau, Jeffrey Chan, Cecile Paris

In the literature, PQA is formulated as a retrieval problem with the goal to search for the most relevant reviews to answer a given product question.

Community Question Answering

Temporal Fusion Network for Temporal Action Localization:Submission to ActivityNet Challenge 2020 (Task E)

no code implementations13 Jun 2020 Zhiwu Qing, Xiang Wang, Yongpeng Sang, Changxin Gao, Shiwei Zhang, Nong Sang

This technical report analyzes a temporal action localization method we used in the HACS competition which is hosted in Activitynet Challenge 2020. The goal of our task is to locate the start time and end time of the action in the untrimmed video, and predict action category. Firstly, we utilize the video-level feature information to train multiple video-level action classification models.

Action Classification Temporal Action Localization

TACNet: Transition-Aware Context Network for Spatio-Temporal Action Detection

no code implementations CVPR 2019 Lin Song, Shiwei Zhang, Gang Yu, Hongbin Sun

In this paper, we define these ambiguous samples as "transitional states", and propose a Transition-Aware Context Network (TACNet) to distinguish transitional states.

Action Detection Frame

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