activity
20242026
collaborators

12 papers

cs.CV2026

BluePixel: Toward Native 4K Agentic Image Editing

Shanyan Guan, Shiyu Li, Xin Li +17

Instruction-driven image editing has reached native 4K, yet how such editors are trained remains undisclosed, and pretraining one from scratch is beyond most teams. The task itself…

cs.CV2026

VINS-120K: Ultra High-Resolution Image Editing with A Large-Scale Dataset

Zhizhou Chen, Shanyan Guan, Zhanxin Gao +6

Directly editing ultra-high-resolution (UHR) images is valuable but underexplored, primarily due to the lack of high-quality data and the challenge in modeling high-frequency textu…

cs.CV2026

RaPD: Resolution-Agnostic Pixel Diffusion via Semantics-Enriched Implicit Representations

Yanhao Ge, Shanyan Guan, Weihao Wang +2

Natural images are continuous, yet most generative models synthesize them on discrete grids, limiting resolution-flexible generation. Continuous neural fields enable resolution-fre…

cs.CV2026

ACE-LoRA: Adaptive Orthogonal Decoupling for Continual Image Editing

Yuehao Liu, Weijia Zhang, Xuanming Shang +4

State-of-the-art diffusion models often rely on parameter-efficient fine-tuning to perform specialized image editing tasks. However, real-world applications require continual adapt…

cs.LG2026

Octopus: History-Free Gradient Orthogonalization for Continual Learning in Multimodal Large Language Models

Yuehao Liu, Shanyan Guan, Weijia Zhang +4

Continual learning in multimodal large language models (MLLMs) aims to sequentially acquire knowledge while mitigating catastrophic forgetting, yet existing methods face inherent l…

cs.CV2026

Guiding a Diffusion Model by Swapping Its Tokens

Weijia Zhang, Yuehao Liu, Shanyan Guan +4

Classifier-Free Guidance (CFG) is a widely used inference-time technique to boost the image quality of diffusion models. Yet, its reliance on text conditions prevents its use in un…

cs.CV2025

UltraHR-100K: Enhancing UHR Image Synthesis with A Large-Scale High-Quality Dataset

Chen Zhao, En Ci, Yunzhe Xu +5

Ultra-high-resolution (UHR) text-to-image (T2I) generation has seen notable progress. However, two key challenges remain : 1) the absence of a large-scale high-quality UHR T2I data…

cs.CV2025

NeoWorld: Neural Simulation of Explorable Virtual Worlds via Progressive 3D Unfolding

Yanpeng Zhao, Shanyan Guan, Yunbo Wang +3

We introduce NeoWorld, a deep learning framework for generating interactive 3D virtual worlds from a single input image. Inspired by the on-demand worldbuilding concept in the scie…

cs.CV2025

Describe, Don't Dictate: Semantic Image Editing with Natural Language Intent

En Ci, Shanyan Guan, Yanhao Ge +5

Despite the progress in text-to-image generation, semantic image editing remains a challenge. Inversion-based algorithms unavoidably introduce reconstruction errors, while instruct…

cs.CV2024

Neural Material Adaptor for Visual Grounding of Intrinsic Dynamics

Junyi Cao, Shanyan Guan, Yanhao Ge +3

While humans effortlessly discern intrinsic dynamics and adapt to new scenarios, modern AI systems often struggle. Current methods for visual grounding of dynamics either use pure…

cs.CV2024

HybridBooth: Hybrid Prompt Inversion for Efficient Subject-Driven Generation

Shanyan Guan, Yanhao Ge, Ying Tai +3

Recent advancements in text-to-image diffusion models have shown remarkable creative capabilities with textual prompts, but generating personalized instances based on specific subj…

cs.CV2024

PostEdit: Posterior Sampling for Efficient Zero-Shot Image Editing

Feng Tian, Yixuan Li, Yichao Yan +3

In the field of image editing, three core challenges persist: controllability, background preservation, and efficiency. Inversion-based methods rely on time-consuming optimization…