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Yanjing Li

Beihang University

23 papers hereh-index 14982 citations35 works total

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

author position
  • first author4
  • middle author17

Across the 21 of 23 papers where every author was matched, so the position is known.

fields
  • cs.CV15
  • cs.LG7
  • cs.CL1
affiliations
  • Beihang University
ORCID 0000-0003-3745-8755
same name
  • Yanjing Li — 4 papers, h 2
  • Yanjing Li — 1 paper
  • Yanjing Li — 1 paper, h 2
  • Yanjing Li — 1 paper, h 5
  • Yanjing Li — 1 paper, h 3
  • Yanjing Li — 1 paper, h 2

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
20192026
most citedQ-ViT: Accurate and Fully Quantized Low-bit Vision Transformer

31 citations · 91 across the 22 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022★ 31 cited

Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer

Yanjing Li, Sheng Xu, Baochang Zhang +3

The large pre-trained vision transformers (ViTs) have demonstrated remarkable performance on various visual tasks, but suffer from expensive computational and memory cost problems…

cs.CV2022★ 2 cited

IDa-Det: An Information Discrepancy-aware Distillation for 1-bit Detectors

Sheng Xu, Yanjing Li, Bohan Zeng +5

Knowledge distillation (KD) has been proven to be useful for training compact object detection models. However, we observe that KD is often effective when the teacher model and stu…

cs.CV2022★ 3 cited

Recurrent Bilinear Optimization for Binary Neural Networks

Sheng Xu, Yanjing Li, Tiancheng Wang +6

Binary Neural Networks (BNNs) show great promise for real-world embedded devices. As one of the critical steps to achieve a powerful BNN, the scale factor calculation plays an esse…

cs.CV2022★ 5 cited

TerViT: An Efficient Ternary Vision Transformer

Sheng Xu, Yanjing Li, Teli Ma +4

Vision transformers (ViTs) have demonstrated great potential in various visual tasks, but suffer from expensive computational and memory cost problems when deployed on resource-con…

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