Search Results for author: Jia-Xing Zhong

Found 10 papers, 7 papers with code

MGDepth: Motion-Guided Cost Volume For Self-Supervised Monocular Depth In Dynamic Scenarios

no code implementations23 Dec 2023 Kaichen Zhou, Jia-Xing Zhong, Jia-Wang Bian, Qian Xie, Jian-Qing Zheng, Niki Trigoni, Andrew Markham

Despite advancements in self-supervised monocular depth estimation, challenges persist in dynamic scenarios due to the dependence on assumptions about a static world.

Computational Efficiency Monocular Depth Estimation +1

DynPoint: Dynamic Neural Point For View Synthesis

1 code implementation NeurIPS 2023 Kaichen Zhou, Jia-Xing Zhong, Sangyun Shin, Kai Lu, Yiyuan Yang, Andrew Markham, Niki Trigoni

The introduction of neural radiance fields has greatly improved the effectiveness of view synthesis for monocular videos.

Uncertainty-aware INVASE: Enhanced Breast Cancer Diagnosis Feature Selection

1 code implementation4 May 2021 Jia-Xing Zhong, Hongbo Zhang

In this paper, we present an uncertainty-aware INVASE to quantify predictive confidence of healthcare problem.

feature selection Uncertainty Quantification

ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network

1 code implementation28 Jun 2019 Zhangheng Li, Jia-Xing Zhong, Jingjia Huang, Tao Zhang, Thomas Li, Ge Li

In recent years, memory-augmented neural networks(MANNs) have shown promising power to enhance the memory ability of neural networks for sequential processing tasks.

SEQUENCE MODELLING WITH AUTO-ADDRESSING AND RECURRENT MEMORY INTEGRATING NETWORKS

no code implementations27 Sep 2018 Zhangheng Li, Jia-Xing Zhong, Jingjia Huang, Tao Zhang, Thomas Li, Ge Li

Processing sequential data with long term dependencies and learn complex transitions are two major challenges in many deep learning applications.

Step-by-step Erasion, One-by-one Collection: A Weakly Supervised Temporal Action Detector

no code implementations9 Jul 2018 Jia-Xing Zhong, Nannan Li, Weijie Kong, Tao Zhang, Thomas H. Li, Ge Li

Weakly supervised temporal action detection is a Herculean task in understanding untrimmed videos, since no supervisory signal except the video-level category label is available on training data.

Action Detection Temporal Localization

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