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Jing Shao

39 papers hereh-index 369.1k citations53 works total

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

author position
  • first author1
  • middle author25
  • last author13

Across the 39 of 39 papers where every author was matched, so the position is known.

fields
  • cs.CV39
same name
  • Jing Shao — 26 papers, h 12
  • Jing Shao — 19 papers, h 13
  • Jing Shao — 18 papers, h 3
  • Jing Shao — 15 papers, h 3
  • Jing Shao — 13 papers, h 9
  • Jing Shao — 12 papers, h 13

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

activity
20172023
most citedSupervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm

128 citations · 932 across the 39 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CV2023★ 40 cited

LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark

Zhenfei Yin, Jiong Wang, Jianjian Cao +9

Large language models have emerged as a promising approach towards achieving general-purpose AI agents. The thriving open-source LLM community has greatly accelerated the developme…

cs.CV2023

Latent Distribution Adjusting for Face Anti-Spoofing

Qinghong Sun, Zhenfei Yin, Yichao Wu +2

With the development of deep learning, the field of face anti-spoofing (FAS) has witnessed great progress. FAS is usually considered a classification problem, where each class is a…

cs.CV2023

Siamese DETR

Zeren Chen, Gengshi Huang, Wei Li +5

Recent self-supervised methods are mainly designed for representation learning with the base model, e.g., ResNets or ViTs. They cannot be easily transferred to DETR, with task-spec…

cs.CV2023★ 6 cited

Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline

Yangguang Li, Bin Huang, Zeren Chen +8

Recently, perception task based on Bird's-Eye View (BEV) representation has drawn more and more attention, and BEV representation is promising as the foundation for next-generation…

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