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Jialiang Wang

19 papers hereh-index 101.5k citations22 works total

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

author position
  • middle author15
  • last author3

Across the 18 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CV19
same name
  • Jialiang Wang — 12 papers, h 9
  • Jialiang Wang — 5 papers, h 2
  • Jialiang Wang — 4 papers, h 3
  • Jialiang Wang — 3 papers, h 7
  • Jialiang Wang — 3 papers, h 0
  • Jialiang Wang — 2 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 citedEmu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

30 citations · 47 across the 18 of their papers we have counts for

collaborators
Showing 2023 · cs.CVShow all

4 papers · 2 filters

cs.CV2023★ 2 cited

FlowVid: Taming Imperfect Optical Flows for Consistent Video-to-Video Synthesis

Feng Liang, Bichen Wu, Jialiang Wang +8

Diffusion models have transformed the image-to-image (I2I) synthesis and are now permeating into videos. However, the advancement of video-to-video (V2V) synthesis has been hampere…

cs.CV2023★ 3 cited

Efficient Quantization Strategies for Latent Diffusion Models

Yuewei Yang, Xiaoliang Dai, Jialiang Wang +2

Latent Diffusion Models (LDMs) capture the dynamic evolution of latent variables over time, blending patterns and multimodality in a generative system. Despite the proficiency of L…

cs.CV2023

ControlRoom3D: Room Generation using Semantic Proxy Rooms

Jonas Schult, Sam Tsai, Lukas Höllein +11

Manually creating 3D environments for AR/VR applications is a complex process requiring expert knowledge in 3D modeling software. Pioneering works facilitate this process by genera…

cs.CV2023★ 30 cited

Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Xiaoliang Dai, Ji Hou, Chih-Yao Ma +23

Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text. However, these pre-trained models often face chal…

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