67 citations · 82 across the 15 of their papers we have counts for
18 papers
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…
Dynamic-in-Few-Step: Unifying Dynamic Computation and Few-Step Distillation for Efficient Video Generation
Yu Cheng, Siyue Yao, Zhongang Qi +3
Video Diffusion Models (VDMs) have demonstrated superior generation quality but suffer from prohibitive computational costs. While recent few-step distillation techniques significa…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
PTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards Video Object Detection
Han Wang, Jun Tang, Xiaodong Liu +3
Recent years have witnessed a trend of applying context frames to boost the performance of object detection as video object detection. Existing methods usually aggregate features a…
NeuroFluid: Fluid Dynamics Grounding with Particle-Driven Neural Radiance Fields
Shanyan Guan, Huayu Deng, Yunbo Wang +1
Deep learning has shown great potential for modeling the physical dynamics of complex particle systems such as fluids. Existing approaches, however, require the supervision of cons…
Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation
Shanyan Guan, Jingwei Xu, Michelle Z. He +3
We consider a new problem of adapting a human mesh reconstruction model to out-of-domain streaming videos, where performance of existing SMPL-based models are significantly affecte…
Bilevel Online Adaptation for Out-of-Domain Human Mesh Reconstruction
Shanyan Guan, Jingwei Xu, Yunbo Wang +2
This paper considers a new problem of adapting a pre-trained model of human mesh reconstruction to out-of-domain streaming videos. However, most previous methods based on the param…
Collaborative Learning for Faster StyleGAN Embedding
Shanyan Guan, Ying Tai, Bingbing Ni +3
The latent code of the recent popular model StyleGAN has learned disentangled representations thanks to the multi-layer style-based generator. Embedding a given image back to the l…