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researcher

Qi Zhao

13 papers hereh-index 6278 citations18 works total

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

author position
  • first author2
  • middle author11

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV12
  • eess.IV1
same name
  • Qi Zhao — 43 papers, h 22
  • Qi Zhao — 22 papers, h 36
  • Qi Zhao — 17 papers, h 13
  • Qi Zhao — 14 papers, h 3
  • Qi Zhao — 11 papers, h 2
  • Qi Zhao — 10 papers, h 8

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 citedMicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation

1 citations · 1 across the 11 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CV2026

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models

Yanting Miao, Yutao Sun, Dexin Wang +8

Visual latent reasoning lets a multimodal large language model (MLLM) create intermediate visual evidence as continuous tokens, avoiding external tools or image generators. However…

cs.CV2026

RealDiffusion: Physics-informed Attention for Multi-character Storybook Generation

Qi Zhao, Jun Chen, Ivor Tsang +1

While modern diffusion models excel at generating diverse single images, extending this to sequential generation reveals a fundamental challenge: balancing narrative dynamism with…

cs.CV2026

Representation Forcing for Bottleneck-Free Unified Multimodal Models

Yuqing Wang, Zhijie Lin, Ceyuan Yang +10

Unified multimodal models (UMMs) aim to handle perception and generation in a single model. Yet existing UMMs still rely on a frozen, separately pretrained VAE for image generation…

cs.CV2026

Context Unrolling in Omni Models

Ceyuan Yang, Zhijie Lin, Yang Zhao +16

We present Omni, a unified multimodal model natively trained on diverse modalities, including text, images, videos, 3D geometry, and hidden representations. We find that such train…

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