15 citations · 15 across the 11 of their papers we have counts for
12 papers · 1 filter
Pixel-Space Diffusion via Observation Operators
Shaojie Guo, Lichen Ma, Haoyang Tong +8
Pixel-space diffusion models directly model image distributions but remain difficult to optimize. Recent methods alleviate this challenge through target reparameterization, while s…
PosterText: Towards Unified Visual Text Generation and Editing for E-commerce Poster
Xiaoan Liu, Lichen Ma, Zipeng Guo +12
Automated e-commerce poster design requires both high-quality poster generation and flexible editing of existing designs. However, most existing methods either target end-to-end po…
TransAnyText: Translating Arbitrary Text in E-commerce Images via Structured Visual Generation
Xiaoan Liu, Lichen Ma, Zipeng Guo +13
Cross-border e-commerce image translation is essential for global retail, where product images, banners, and detail pages need to be produced in different languages. Existing metho…
GMO-EDIT: Grounded Multi-Operation Editing for E-Commerce Images
Zipeng Guo, Xiaoan Liu, Lichen Ma +9
Real-world e-commerce image editing often requires multiple, localized, and auditable operations rather than global restyling. This compositional nature poses a dual challenge: mod…
PixelU: A U-Shaped Transformer for Efficient End-to-End Pixel Diffusion
Zipeng Guo, Lichen Ma, Yu He +4
End-to-end pixel-space diffusion models bypass the lossy compression of Latent Diffusion Models (LDMs) but struggle to jointly model low-frequency semantics and high-frequency sign…
HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion
Yu He, Lichen Ma, Zipeng Guo +5
Pixel-space diffusion models bypass the reconstruction bottleneck of Variational Autoencoders (VAEs) but face a fundamental "granularity dilemma": capturing global semantics favors…
FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion
Lichen Ma, Zipeng Guo, Yu He +5
To circumvent the inherent fidelity bottlenecks and optimization misalignment of VAE-based latent diffusion, pixel-space diffusion models have emerged as a compelling end-to-end pa…
KD-CVG: A Knowledge-Driven Approach for Creative Video Generation
Linkai Liu, Wei Feng, Xi Zhao +9
Creative Generation (CG) leverages generative models to automatically produce advertising content that highlights product features, and it has been a significant focus of recent re…
UM-Text: A Unified Multimodal Model for Image Understanding and Visual Text Editing
Lichen Ma, Xiaolong Fu, Gaojing Zhou +6
With the rapid advancement of image generation, visual text editing using natural language instructions has received increasing attention. The main challenge of this task is to ful…
RePainter: Empowering E-commerce Object Removal via Spatial-matting Reinforcement Learning
Zipeng Guo, Lichen Ma, Xiaolong Fu +13
In web data, product images are central to boosting user engagement and advertising efficacy on e-commerce platforms, yet the intrusive elements such as watermarks and promotional…
Dynamic-TreeRPO: Breaking the Independent Trajectory Bottleneck with Structured Sampling
Xiaolong Fu, Lichen Ma, Zipeng Guo +9
The integration of Reinforcement Learning (RL) into flow matching models for text-to-image (T2I) generation has driven substantial advances in generation quality. However, these ga…
Where, What, Why: Towards Explainable Driver Attention Prediction
Yuchen Zhou, Jiayu Tang, Xiaoyan Xiao +6
Modeling task-driven attention in driving is a fundamental challenge for both autonomous vehicles and cognitive science. Existing methods primarily predict where drivers look by ge…