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researcher

Y. Qiao

33 papers hereh-index 3010.3k citations46 works total

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

author position
  • middle author25
  • last author6

Across the 31 of 33 papers where every author was matched, so the position is known.

fields
  • cs.CV30
  • cs.LG1
  • cs.MM1
  • cs.RO1
same name
  • Y. Qiao — 106 papers, h 60
  • Y. Qiao — 87 papers, h 85
  • Y. Qiao — 9 papers, h 3
  • Y. Qiao — 7 papers, h 39
  • Y. Qiao — 4 papers, h 5
  • Y. Qiao — 2 papers, h 23

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
20212024
most citedLLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

172 citations · 1.2k across the 32 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CV2021★ 11 cited

Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results

Liang Pan, Tong Wu, Zhongang Cai +26

As real-scanned point clouds are mostly partial due to occlusions and viewpoints, reconstructing complete 3D shapes based on incomplete observations becomes a fundamental problem f…

cs.CV2021

PointCLIP: Point Cloud Understanding by CLIP

Renrui Zhang, Ziyu Guo, Wei Zhang +6

Recently, zero-shot and few-shot learning via Contrastive Vision-Language Pre-training (CLIP) have shown inspirational performance on 2D visual recognition, which learns to match i…

cs.CV2021★ 128 cited

Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Renrui Zhang, Rongyao Fang, Wei Zhang +5

Contrastive Vision-Language Pre-training, known as CLIP, has provided a new paradigm for learning visual representations by using large-scale contrastive image-text pairs. It shows…

cs.CV2021★ 113 cited

CLIP-Adapter: Better Vision-Language Models with Feature Adapters

Peng Gao, Shijie Geng, Renrui Zhang +5

Large-scale contrastive vision-language pre-training has shown significant progress in visual representation learning. Unlike traditional visual systems trained by a fixed set of d…

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