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20222026
most citedFast Object Placement Assessment

5 citations · 6 across the 15 of their papers we have counts for

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13 papers · 1 filter

cs.CV2026

Pixel-wise Geo-registration of Drone and Satellite Images

Qingyang Liu, David G Shatwell, Parth Parag Kulkarni +1

Pixel-level cross-view geo-registration aims to align a query image (e.g., drone) to a geo-referenced satellite map so that every query pixel can be mapped to real-world GPS coordi…

cs.CV2026

Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners

Qingyang Liu, Bingjie Gao, Canmiao Fu +9

Recent unified models integrate multimodal understanding and generation within a single framework. However, an "understanding-generation gap" persists, where models can capture use…

cs.CV2026

Reflection Generation for Composite Image Using Diffusion Model

Haonan Zhao, Qingyang Liu, Jiaxuan Chen +1

Image composition involves inserting a foreground object into the background while synthesizing environment-consistent effects such as shadows and reflections. Although shadow gene…

cs.CV2025

TiViBench: Benchmarking Think-in-Video Reasoning for Video Generative Models

Harold Haodong Chen, Disen Lan, Wen-Jie Shu +10

The rapid evolution of video generative models has shifted their focus from producing visually plausible outputs to tackling tasks requiring physical plausibility and logical consi…

cs.CV2025

UnicEdit-10M: A Dataset and Benchmark Breaking the Scale-Quality Barrier via Unified Verification for Reasoning-Enriched Edits

Keming Ye, Zhipeng Huang, Canmiao Fu +7

With the rapid advances of powerful multimodal models such as GPT-4o, Nano Banana, and Seedream 4.0 in Image Editing, the performance gap between closed-source and open-source mode…

cs.CV2025

DToM: Decider-Guided Dynamic Token Merging for Accelerating Diffusion MLLMs

Shuochen Chang, Xiaofeng Zhang, Qingyang Liu +1

Diffusion-based multimodal large language models (Diffusion MLLMs) have recently demonstrated impressive non-autoregressive generative capabilities across vision-and-language tasks…