Search Results for author: Terence Sim

Found 6 papers, 2 papers with code

Contrastive predictive coding for Anomaly Detection in Multi-variate Time Series Data

no code implementations8 Feb 2022 THEIVENDIRAM PRANAVAN, Terence Sim, ArulMurugan Ambikapathi, Savitha Ramasamy

Next, the latent representations for the succeeding instants obtained through non-linear transformations of these context vectors, are contrasted with the latent representations of the encoder for the multi-variables such that the density for the positive pair is maximized.

Anomaly Detection Time Series

Continual Learning with Delayed Feedback

no code implementations25 Sep 2019 THEIVENDIRAM PRANAVAN, Terence Sim

This work proposes a model-agnostic continual learning framework which can be used with neural networks as well as decision trees to incorporate continual learning.

Continual Learning

Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing

2 code implementations10 Apr 2018 Jian Zhao, Jianshu Li, Yu Cheng, Li Zhou, Terence Sim, Shuicheng Yan, Jiashi Feng

Despite the noticeable progress in perceptual tasks like detection, instance segmentation and human parsing, computers still perform unsatisfactorily on visually understanding humans in crowded scenes, such as group behavior analysis, person re-identification and autonomous driving, etc.

Autonomous Driving Instance Segmentation +4

Integrated Face Analytics Networks through Cross-Dataset Hybrid Training

no code implementations16 Nov 2017 Jianshu Li, Shengtao Xiao, Fang Zhao, Jian Zhao, Jianan Li, Jiashi Feng, Shuicheng Yan, Terence Sim

Specifically, iFAN achieves an overall F-score of 91. 15% on the Helen dataset for face parsing, a normalized mean error of 5. 81% on the MTFL dataset for facial landmark localization and an accuracy of 45. 73% on the BNU dataset for emotion recognition with a single model.

Face Alignment Face Parsing +1

Multiple-Human Parsing in the Wild

2 code implementations19 May 2017 Jianshu Li, Jian Zhao, Yunchao Wei, Congyan Lang, Yidong Li, Terence Sim, Shuicheng Yan, Jiashi Feng

To address the multi-human parsing problem, we introduce a new multi-human parsing (MHP) dataset and a novel multi-human parsing model named MH-Parser.

Multi-Human Parsing

Correlation Filters with Limited Boundaries

no code implementations CVPR 2015 Hamed Kiani Galoogahi, Terence Sim, Simon Lucey

In this paper, we propose a novel approach to correlation filter estimation that: (i) takes advantage of inherent computational redundancies in the frequency domain, and (ii) dramatically reduces boundary effects.

Object Tracking

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