Search Results for author: Ding Ma

Found 6 papers, 1 papers with code

Tracking by Natural Language Specification with Long Short-term Context Decoupling

no code implementations ICCV 2023 Ding Ma, Xiangqian Wu

The main challenge of Tracking by Natural Language Specification (TNL) is to predict the movement of the target object by giving two heterogeneous information, e. g., one is the static description of the main characteristics of a video contained in the textual query, i. e., long-term context; the other one is an image patch containing the object and its surroundings cropped from the current frame, i. e., the search area.

CapsuleRRT: Relationships-Aware Regression Tracking via Capsules

no code implementations CVPR 2021 Ding Ma, Xiangqian Wu

Regression tracking has gained more and more attention thanks to its easy-to-implement characteristics, while existing regression trackers rarely consider the relationships between the object parts and the complete object.

Image Classification Knowledge Distillation +2

A Julia implementation of Algorithm NCL for constrained optimization

no code implementations6 Jan 2021 Ding Ma, Dominique Orban, Michael A. Saunders

We give numerical results from a Julia implementation of Algorithm NCL on tax policy models that do not satisfy the LICQ, and on nonlinear least-squares problems and general problems from the CUTEst test set.

Optimization and Control Numerical Analysis Numerical Analysis

TCDCaps: Visual Tracking via Cascaded Dense Capsules

no code implementations26 Feb 2019 Ding Ma, Xiangqian Wu

The critical challenge in tracking-by-detection framework is how to avoid drift problem during online learning, where the robust features for a variety of appearance changes are difficult to be learned and a reasonable intersection over union (IoU) threshold that defines the true/false positives is hard to set.

Visual Tracking

Defining Least Community as a Homogeneous Group in Complex Networks

no code implementations1 Feb 2015 Bin Jiang, Ding Ma

This notion of far more small things than large ones constitutes a new fundamental way of thinking for community detection.

Physics and Society Social and Information Networks Adaptation and Self-Organizing Systems

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