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Zhiyu Tan

32 papers hereh-index 14958 citations42 works total

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

author position
  • first author7
  • middle author22

Across the 29 of 32 papers where every author was matched, so the position is known.

fields
  • cs.CV24
  • eess.IV4
  • cs.LG2
  • cs.AI1
  • math.OC1
same name
  • Zhiyu Tan — 1 paper
  • Zhiyu Tan — 1 paper

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
20202026
most citedGiraffeDet: A Heavy-Neck Paradigm for Object Detection

78 citations · 177 across the 32 of their papers we have counts for

collaborators
Showing eess.IVShow all

4 papers · 1 filter

eess.IV2022★ 14 cited

Entroformer: A Transformer-based Entropy Model for Learned Image Compression

Yichen Qian, Ming Lin, Xiuyu Sun +2

One critical component in lossy deep image compression is the entropy model, which predicts the probability distribution of the quantized latent representation in the encoding and…

eess.IV2021★ 18 cited

Interpolation variable rate image compression

Zhenhong Sun, Zhiyu Tan, Xiuyu Sun +4

Compression standards have been used to reduce the cost of image storage and transmission for decades. In recent years, learned image compression methods have been proposed and ach…

eess.IV2021★ 6 cited

Spatiotemporal Entropy Model is All You Need for Learned Video Compression

Zhenhong Sun, Zhiyu Tan, Xiuyu Sun +4

The framework of dominant learned video compression methods is usually composed of motion prediction modules as well as motion vector and residual image compression modules, suffer…

eess.IV2020★ 35 cited

Learning Accurate Entropy Model with Global Reference for Image Compression

Yichen Qian, Zhiyu Tan, Xiuyu Sun +5

In recent deep image compression neural networks, the entropy model plays a critical role in estimating the prior distribution of deep image encodings. Existing methods combine hyp…

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