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Songyang Zhang

University of Rochester

21 papers hereh-index 174.6k citations26 works total

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

author position
  • first author7
  • middle author14

Across the 21 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CV17
  • cs.CL1
  • cs.LG1
  • cs.MM1
  • cs.SI1
affiliations
  • University of Rochester
Homepage
same name
  • Songyang Zhang — 39 papers, h 22
  • Songyang Zhang — 24 papers, h 20
  • Songyang Zhang — 12 papers
  • Songyang Zhang — 9 papers, h 5
  • Songyang Zhang — 6 papers, h 2
  • Songyang Zhang — 6 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
20192023
most citedMake-A-Video: Text-to-Video Generation without Text-Video Data

315 citations · 481 across the 21 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CV2023★ 3 cited

Learning Referring Video Object Segmentation from Weak Annotation

Wangbo Zhao, Kepan Nan, Songyang Zhang +3

Referring video object segmentation (RVOS) is a task that aims to segment the target object in all video frames based on a sentence describing the object. Although existing RVOS me…

cs.CV2023★ 2 cited

Unveiling Cross Modality Bias in Visual Question Answering: A Causal View with Possible Worlds VQA

Ali Vosoughi, Shijian Deng, Songyang Zhang +3

To increase the generalization capability of VQA systems, many recent studies have tried to de-bias spurious language or vision associations that shortcut the question or image to…

cs.CV2023

TG-VQA: Ternary Game of Video Question Answering

Hao Li, Peng Jin, Zesen Cheng +5

Video question answering aims at answering a question about the video content by reasoning the alignment semantics within them. However, since relying heavily on human instructions…

cs.CV2023★ 27 cited

Latent-Shift: Latent Diffusion with Temporal Shift for Efficient Text-to-Video Generation

Jie An, Songyang Zhang, Harry Yang +4

We propose Latent-Shift -- an efficient text-to-video generation method based on a pretrained text-to-image generation model that consists of an autoencoder and a U-Net diffusion m…

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