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Rong Jin

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Rong Jin — 42 papers, h 76
  • Rong Jin — 15 papers
  • Rong Jin — 7 papers
  • Rong Jin — 2 papers
  • Rong Jin — 2 papers
  • Rong Jin — 1 paper, h 22

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedHybrid Relation Guided Set Matching for Few-shot Action Recognition

7 citations · 13 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2022★ 6 cited

An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation

Ziquan Liu, Yi Xu, Yuanhong Xu +5

The performance of machine learning models under distribution shift has been the focus of the community in recent years. Most of current methods have been proposed to improve the r…

cs.CV2022★ 7 cited

Hybrid Relation Guided Set Matching for Few-shot Action Recognition

Xiang Wang, Shiwei Zhang, Zhiwu Qing +5

Current few-shot action recognition methods reach impressive performance by learning discriminative features for each video via episodic training and designing various temporal ali…

cs.CV2022

Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency

Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +6

Natural videos provide rich visual contents for self-supervised learning. Yet most existing approaches for learning spatio-temporal representations rely on manually trimmed videos,…

cs.CV2021

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

Ming Lin, Pichao Wang, Zhenhong Sun +5

Accuracy predictor is a key component in Neural Architecture Search (NAS) for ranking architectures. Building a high-quality accuracy predictor usually costs enormous computation.…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.