Search Results for author: Bineng Zhong

Found 25 papers, 14 papers with code

Autoregressive Queries for Adaptive Tracking with Spatio-TemporalTransformers

no code implementations15 Mar 2024 Jinxia Xie, Bineng Zhong, Zhiyi Mo, Shengping Zhang, Liangtao Shi, Shuxiang Song, Rongrong Ji

Firstly, we introduce a set of learnable and autoregressive queries to capture the instantaneous target appearance changes in a sliding window fashion.

Visual Tracking

End-to-End Human Instance Matting

1 code implementation3 Mar 2024 Qinglin Liu, Shengping Zhang, Quanling Meng, Bineng Zhong, Peiqiang Liu, Hongxun Yao

Finally, an instance matting network decodes the image features and united semantics guidance to predict all instance-level alpha mattes.

Image Matting Instance Segmentation +1

Explicit Visual Prompts for Visual Object Tracking

1 code implementation6 Jan 2024 Liangtao Shi, Bineng Zhong, Qihua Liang, Ning li, Shengping Zhang, Xianxian Li

Specifically, we utilize spatio-temporal tokens to propagate information between consecutive frames without focusing on updating templates.

Object Visual Object Tracking +1

ODTrack: Online Dense Temporal Token Learning for Visual Tracking

1 code implementation3 Jan 2024 Yaozong Zheng, Bineng Zhong, Qihua Liang, Zhiyi Mo, Shengping Zhang, Xianxian Li

To alleviate the above problem, we propose a simple, flexible and effective video-level tracking pipeline, named \textbf{ODTrack}, which densely associates the contextual relationships of video frames in an online token propagation manner.

Semi-Supervised Video Object Segmentation Visual Object Tracking +1

Autoregressive Queries for Adaptive Tracking with Spatio-Temporal Transformers

no code implementations CVPR 2024 Jinxia Xie, Bineng Zhong, Zhiyi Mo, Shengping Zhang, Liangtao Shi, Shuxiang Song, Rongrong Ji

Firstly we introduce a set of learnable and autoregressive queries to capture the instantaneous target appearance changes in a sliding window fashion.

Visual Tracking

Fourier Priors-Guided Diffusion for Zero-Shot Joint Low-Light Enhancement and Deblurring

no code implementations CVPR 2024 Xiaoqian Lv, Shengping Zhang, Chenyang Wang, Yichen Zheng, Bineng Zhong, Chongyi Li, Liqiang Nie

Existing joint low-light enhancement and deblurring methods learn pixel-wise mappings from paired synthetic data which results in limited generalization in real-world scenes.


Towards Unified Token Learning for Vision-Language Tracking

1 code implementation27 Aug 2023 Yaozong Zheng, Bineng Zhong, Qihua Liang, Guorong Li, Rongrong Ji, Xianxian Li

In this paper, we present a simple, flexible and effective vision-language (VL) tracking pipeline, termed \textbf{MMTrack}, which casts VL tracking as a token generation task.

Visualizing and Understanding Patch Interactions in Vision Transformer

no code implementations11 Mar 2022 Jie Ma, Yalong Bai, Bineng Zhong, Wei zhang, Ting Yao, Tao Mei

Vision Transformer (ViT) has become a leading tool in various computer vision tasks, owing to its unique self-attention mechanism that learns visual representations explicitly through cross-patch information interactions.

Long-Range Feature Propagating for Natural Image Matting

1 code implementation25 Sep 2021 Qinglin Liu, Haozhe Xie, Shengping Zhang, Bineng Zhong, Rongrong Ji

Finally, we use the matting module which takes the image, trimap and context features to estimate the alpha matte.

Ranked #6 on Image Matting on Composition-1K (using extra training data)

Image Matting

Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification

1 code implementation CVPR 2021 Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji

In this paper, we propose a joint Modality and Pattern Alignment Network (MPANet) to discover cross-modality nuances in different patterns for visible-infrared person Re-ID, which introduces a modality alleviation module and a pattern alignment module to jointly extract discriminative features.

Person Re-Identification

Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy

1 code implementation CVPR 2021 Zikai Zhang, Bineng Zhong, Shengping Zhang, Zhenjun Tang, Xin Liu, Zhaoxiang Zhang

A practical long-term tracker typically contains three key properties, i. e. an efficient model design, an effective global re-detection strategy and a robust distractor awareness mechanism.

Multiple Object Tracking Philosophy

Learning to Filter: Siamese Relation Network for Robust Tracking

1 code implementation CVPR 2021 Siyuan Cheng, Bineng Zhong, Guorong Li, Xin Liu, Zhenjun Tang, Xianxian Li, Jing Wang

RD performs in a meta-learning way to obtain a learning ability to filter the distractors from the background while RM aims to effectively integrate the proposed RD into the Siamese framework to generate accurate tracking result.

Meta-Learning Relation +1

EC-DARTS: Inducing Equalized and Consistent Optimization Into DARTS

no code implementations ICCV 2021 Qinqin Zhou, Xiawu Zheng, Liujuan Cao, Bineng Zhong, Teng Xi, Gang Zhang, Errui Ding, Mingliang Xu, Rongrong Ji

EC-DARTS decouples different operations based on their categories to optimize the operation weights so that the operation gap between them is shrinked.

Projection & Probability-Driven Black-Box Attack

1 code implementation CVPR 2020 Jie Li, Rongrong Ji, Hong Liu, Jianzhuang Liu, Bineng Zhong, Cheng Deng, Qi Tian

For reducing the solution space, we first model the adversarial perturbation optimization problem as a process of recovering frequency-sparse perturbations with compressed sensing, under the setting that random noise in the low-frequency space is more likely to be adversarial.

Siamese Box Adaptive Network for Visual Tracking

2 code implementations CVPR 2020 Zedu Chen, Bineng Zhong, Guorong Li, Shengping Zhang, Rongrong Ji

Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-defined anchor boxes to accurately estimate the scale and aspect ratio of a target.

Visual Tracking

Residual Non-local Attention Networks for Image Restoration

2 code implementations ICLR 2019 Yulun Zhang, Kunpeng Li, Kai Li, Bineng Zhong, Yun Fu

To address this issue, we design local and non-local attention blocks to extract features that capture the long-range dependencies between pixels and pay more attention to the challenging parts.

Demosaicking Image Denoising +1

Representative Task Self-selection for Flexible Clustered Lifelong Learning

no code implementations6 Mar 2019 Gan Sun, Yang Cong, Qianqian Wang, Bineng Zhong, Yun Fu

Consider the lifelong machine learning paradigm whose objective is to learn a sequence of tasks depending on previous experiences, e. g., knowledge library or deep network weights.

Model Optimization Multi-Task Learning

Predictive Local Smoothness for Stochastic Gradient Methods

no code implementations ICLR 2019 Jun Li, Hongfu Liu, Bineng Zhong, Yue Wu, Yun Fu

To address this problem, we propose a simple yet effective method for improving stochastic gradient methods named predictive local smoothness (PLS).

Residual Dense Network for Image Super-Resolution

16 code implementations CVPR 2018 Yulun Zhang, Yapeng Tian, Yu Kong, Bineng Zhong, Yun Fu

In this paper, we propose a novel residual dense network (RDN) to address this problem in image SR. We fully exploit the hierarchical features from all the convolutional layers.

Color Image Denoising Image Super-Resolution

An Effective Unconstrained Correlation Filter and Its Kernelization for Face Recognition

no code implementations25 Mar 2016 Yan Yan, Hanzi Wang, Cuihua Li, Chenhui Yang, Bineng Zhong

In this paper, an effective unconstrained correlation filter called Uncon- strained Optimal Origin Tradeoff Filter (UOOTF) is presented and applied to robust face recognition.

Face Recognition Robust Face Recognition

Understanding Image Structure via Hierarchical Shape Parsing

no code implementations CVPR 2015 Xian-Ming Liu, Rongrong Ji, Changhu Wang, Wei Liu, Bineng Zhong, Thomas S. Huang

A hierarchical shape parsing strategy is proposed to partition and organize image components into a hierarchical structure in the scale space.

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