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Zihao Wang

7 papers hereh-index 9826 citations22 works total

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

author position
  • first author4
  • middle author3

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG3
same name
  • Zihao Wang — 25 papers, h 16
  • Zihao Wang — 19 papers, h 15
  • Zihao Wang — 17 papers, h 7
  • Zihao Wang — 14 papers, h 19
  • Zihao Wang — 11 papers, h 5
  • Zihao Wang — 11 papers, h 3

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
20192022
most citedCLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP

31 citations · 62 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2022★ 31 cited

CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP

Zihao Wang, Wei Liu, Qian He +2

Training a text-to-image generator in the general domain (e.g., Dall.e, CogView) requires huge amounts of paired text-image data, which is too expensive to collect. In this paper,…

cs.CV2020★ 7 cited

PV-NAS: Practical Neural Architecture Search for Video Recognition

Zihao Wang, Chen Lin, Lu Sheng +2

Recently, deep learning has been utilized to solve video recognition problem due to its prominent representation ability. Deep neural networks for video tasks is highly customized…

cs.CV2019

CAMP: Cross-Modal Adaptive Message Passing for Text-Image Retrieval

Zihao Wang, Xihui Liu, Hongsheng Li +4

Text-image cross-modal retrieval is a challenging task in the field of language and vision. Most previous approaches independently embed images and sentences into a joint embedding…

cs.CV2019★ 24 cited

Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing

Xihui Liu, Zihao Wang, Jing Shao +2

Referring expression grounding aims at locating certain objects or persons in an image with a referring expression, where the key challenge is to comprehend and align various types…

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