1 citations · 2 across the 11 of their papers we have counts for
13 papers
InnoText: A Unified Model for Visual Text Generation and Editing
Haowei Liu, Runze He, Jian Lu +10
Diffusion models have recently achieved remarkable success in high-fidelity image synthesis, yet their application to visual text generation and editing remains relatively underexp…
Keep It in Mind: User Centric Continual Spatial Intelligence Reasoning in Egocentric Video Streams
Yun Wang, Junbin Xiao, Han Lyu +6
We introduce UCS-Bench, a dataset spanning 170+ hours of egocentric visual observations with 8.1K+ timestamped questions for diagnosing User-Centric Continual Spatial intelligence…
FedCVU: Federated Learning for Cross-View Video Understanding
Shenghan Zhang, Run Ling, Ke Cao +2
Federated learning (FL) has emerged as a promising paradigm for privacy-preserving multi-camera video understanding. However, applying FL to cross-view scenarios faces three major…
InnoAds-Composer: Efficient Condition Composition for E-Commerce Poster Generation
Yuxin Qin, Ke Cao, Haowei Liu +13
E-commerce product poster generation aims to automatically synthesize a single image that effectively conveys product information by presenting a subject, text, and a designed styl…
Cross-Scale Pansharpening via ScaleFormer and the PanScale Benchmark
Ke Cao, Xuanhua He, Xueheng Li +7
Pansharpening aims to generate high-resolution multi-spectral images by fusing the spatial detail of panchromatic images with the spectral richness of low-resolution MS data. Howev…
StyMam: A Mamba-Based Generator for Artistic Style Transfer
Zhou Hong, Ning Dong, Yicheng Di +8
Image style transfer aims to integrate the visual patterns of a specific artistic style into a content image while preserving its content structure. Existing methods mainly rely on…
MoFu: Scale-Aware Modulation and Fourier Fusion for Multi-Subject Video Generation
Run Ling, Ke Cao, Jian Lu +15
Multi-subject video generation aims to synthesize videos from textual prompts and multiple reference images, ensuring that each subject preserves natural scale and visual fidelity.…
Lay2Story: Extending Diffusion Transformers for Layout-Togglable Story Generation
Ao Ma, Jiasong Feng, Ke Cao +4
Storytelling tasks involving generating consistent subjects have gained significant attention recently. However, existing methods, whether training-free or training-based, continue…
Video-EM: Event-Centric Episodic Memory for Long-Form Video Understanding
Yun Wang, Long Zhang, Jingren Liu +9
Video Large Language Models (Video-LLMs) have shown strong video understanding, yet their application to long-form videos remains constrained by limited context windows. A common w…
Learning Robust Stereo Matching in the Wild with Selective Mixture-of-Experts
Yun Wang, Longguang Wang, Chenghao Zhang +6
Recently, learning-based stereo matching networks have advanced significantly. However, they often lack robustness and struggle to achieve impressive cross-domain performance due t…
U-StyDiT: Ultra-high Quality Artistic Style Transfer Using Diffusion Transformers
Zhanjie Zhang, Ao Ma, Ke Cao +6
Ultra-high quality artistic style transfer refers to repainting an ultra-high quality content image using the style information learned from the style image. Existing artistic styl…
WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation
Jing Wang, Ao Ma, Ke Cao +9
Recent rapid advancements in text-to-video (T2V) generation, such as SoRA and Kling, have shown great potential for building world simulators. However, current T2V models struggle…
RelaCtrl: Relevance-Guided Efficient Control for Diffusion Transformers
Ke Cao, Jing Wang, Ao Ma +11
The Diffusion Transformer plays a pivotal role in advancing text-to-image and text-to-video generation, owing primarily to its inherent scalability. However, existing controlled di…