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Chen Sun

7 papers hereh-index 6137 citations9 works total

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

author position
  • middle author3
  • last author4

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

fields
  • cs.CV7
same name
  • Chen Sun — 65 papers, h 45
  • Chen Sun — 19 papers, h 10
  • Chen Sun — 15 papers, h 6
  • Chen Sun — 8 papers, h 6
  • Chen Sun — 6 papers, h 1
  • Chen Sun — 5 papers, 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
20232026
most citedPre-trained Vision-Language Models Learn Discoverable Visual Concepts

1 citations · 1 across the 7 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

4 papers · 2 filters

cs.CV2024

MotiF: Making Text Count in Image Animation with Motion Focal Loss

Shijie Wang, Samaneh Azadi, Rohit Girdhar +3

Text-Image-to-Video (TI2V) generation aims to generate a video from an image following a text description, which is also referred to as text-guided image animation. Most existing m…

cs.CV2024

Do Pre-trained Vision-Language Models Encode Object States?

Kaleb Newman, Shijie Wang, Yuan Zang +2

For a vision-language model (VLM) to understand the physical world, such as cause and effect, a first step is to capture the temporal dynamics of the visual world, for example how…

cs.CV2024

Learning Visual Grounding from Generative Vision and Language Model

Shijie Wang, Dahun Kim, Ali Taalimi +2

Visual grounding tasks aim to localize image regions based on natural language references. In this work, we explore whether generative VLMs predominantly trained on image-text data…

cs.CV2024★ 1 cited

Pre-trained Vision-Language Models Learn Discoverable Visual Concepts

Yuan Zang, Tian Yun, Hao Tan +2

Do vision-language models (VLMs) pre-trained to caption an image of a "durian" learn visual concepts such as "brown" (color) and "spiky" (texture) at the same time? We aim to answe…

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