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researcher

Gen Li

4 papers hereh-index 21.1k citations4 works total

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

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Gen Li — 23 papers, h 14
  • Gen Li — 20 papers, h 16
  • Gen Li — 18 papers, h 2
  • Gen Li — 13 papers, h 5
  • Gen Li — 12 papers, h 6
  • Gen Li — 9 papers, h 18

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
20192023
most citedUnicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training

116 citations · 121 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 2 cited

LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding

Gen Li, Varun Jampani, Deqing Sun +1

Humans excel at acquiring knowledge through observation. For example, we can learn to use new tools by watching demonstrations. This skill is fundamental for intelligent systems to…

cs.CV2021★ 1 cited

SuperStyleNet: Deep Image Synthesis with Superpixel Based Style Encoder

Jonghyun Kim, Gen Li, Cheolkon Jung +1

Existing methods for image synthesis utilized a style encoder based on stacks of convolutions and pooling layers to generate style codes from input images. However, the encoded vec…

cs.CV2019★ 116 cited

Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training

Gen Li, Nan Duan, Yuejian Fang +3

We propose Unicoder-VL, a universal encoder that aims to learn joint representations of vision and language in a pre-training manner. Borrow ideas from cross-lingual pre-trained mo…

cs.CV2019★ 2 cited

Deep Reason: A Strong Baseline for Real-World Visual Reasoning

Chenfei Wu, Yanzhao Zhou, Gen Li +3

This paper presents a strong baseline for real-world visual reasoning (GQA), which achieves 60.93% in GQA 2019 challenge and won the sixth place. GQA is a large dataset with 22M qu…

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