1 citations · 4 across the 19 of their papers we have counts for
22 papers
UltraDiff: Transferring High-Fidelity Priors to Compressed Latent Spaces for High-Resolution Image Generation
Jingjing Ren, Haitian Zheng, Haoyu Chen +5
High-resolution synthesis with Latent Diffusion Models (LDMs) faces a fundamental trade-off between computational cost and generative fidelity. This trade off is largely governed b…
SupGRPO: Enhancing GRPO with Matching-based Online SFT for Text Spotting
Xudong Xie, Yuzhe Li, Jing Shi +3
Text spotting requires both accurate text recognition and precise spatial localization. Current specialised spotters excel at predicting tight bounding boxes in natural scenes, but…
PixelControl: Fine-Grained Condition Fidelity in Text-to-Image Diffusion
Xin Lin, Haodong Li, Zhifei Zhang +5
Controllable text-to-image diffusion models can often follow the global layout of spatial conditions, yet still violate fine-grained structures such as object boundaries, thin cont…
End-to-End Direction-Aware Keyword Spotting with Spatial Priors in Noisy Environments
Rui Wang, Zhifei Zhang, Yu Gao +2
Keyword spotting (KWS) is crucial for many speech-driven applications, but robust KWS in noisy environments remains challenging. Conventional systems often rely on single-channel i…
Both Semantics and Reconstruction Matter: Making Representation Encoders Ready for Text-to-Image Generation and Editing
Shilong Zhang, He Zhang, Zhifei Zhang +11
Modern Latent Diffusion Models (LDMs) typically operate in low-level Variational Autoencoder (VAE) latent spaces that are primarily optimized for pixel-level reconstruction. To uni…
DiffusionBrowser: Interactive Diffusion Previews via Multi-Branch Decoders
Susung Hong, Chongjian Ge, Zhifei Zhang +1
Video diffusion models have revolutionized generative video synthesis, but they are imprecise, slow, and can be opaque during generation -- keeping users in the dark for a prolonge…
HBridge: H-Shape Bridging of Heterogeneous Experts for Unified Multimodal Understanding and Generation
Xiang Wang, Zhifei Zhang, He Zhang +11
Recent unified models integrate understanding experts (e.g., LLMs) with generative experts (e.g., diffusion models), achieving strong multimodal performance. However, recent advanc…
EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning
Xuan Ju, Tianyu Wang, Yuqian Zhou +11
Recent advances in foundation models highlight a clear trend toward unification and scaling, showing emergent capabilities across diverse domains. While image generation and editin…
OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions
Yuanhao Cai, He Zhang, Xi Chen +11
Existing feedforward subject-driven video customization methods mainly study single-subject scenarios due to the difficulty of constructing multi-subject training data pairs. Anoth…
ZipIR: Latent Pyramid Diffusion Transformer for High-Resolution Image Restoration
Yongsheng Yu, Haitian Zheng, Zhifei Zhang +7
Recent progress in generative models has significantly improved image restoration capabilities, particularly through powerful diffusion models that offer remarkable recovery of sem…
TurboFill: Adapting Few-step Text-to-image Model for Fast Image Inpainting
Liangbin Xie, Daniil Pakhomov, Zhonghao Wang +8
This paper introduces TurboFill, a fast image inpainting model that enhances a few-step text-to-image diffusion model with an inpainting adapter for high-quality and efficient inpa…
Multitwine: Multi-Object Compositing with Text and Layout Control
Gemma Canet Tarrés, Zhe Lin, Zhifei Zhang +4
We introduce the first generative model capable of simultaneous multi-object compositing, guided by both text and layout. Our model allows for the addition of multiple objects with…
TransPixeler: Advancing Text-to-Video Generation with Transparency
Luozhou Wang, Yijun Li, Zhifei Chen +5
Text-to-video generative models have made significant strides, enabling diverse applications in entertainment, advertising, and education. However, generating RGBA video, which inc…
Generative Video Propagation
Shaoteng Liu, Tianyu Wang, Jui-Hsien Wang +8
Large-scale video generation models have the inherent ability to realistically model natural scenes. In this paper, we demonstrate that through a careful design of a generative vid…
UniReal: Universal Image Generation and Editing via Learning Real-world Dynamics
Xi Chen, Zhifei Zhang, He Zhang +10
We introduce UniReal, a unified framework designed to address various image generation and editing tasks. Existing solutions often vary by tasks, yet share fundamental principles:…
Refine-by-Align: Reference-Guided Artifacts Refinement through Semantic Alignment
Yizhi Song, Liu He, Zhifei Zhang +8
Personalized image generation has emerged from the recent advancements in generative models. However, these generated personalized images often suffer from localized artifacts such…
FINECAPTION: Compositional Image Captioning Focusing on Wherever You Want at Any Granularity
Hang Hua, Qing Liu, Lingzhi Zhang +5
The advent of large Vision-Language Models (VLMs) has significantly advanced multimodal tasks, enabling more sophisticated and accurate reasoning across various applications, inclu…
Baking Gaussian Splatting into Diffusion Denoiser for Fast and Scalable Single-stage Image-to-3D Generation and Reconstruction
Yuanhao Cai, He Zhang, Kai Zhang +12
Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt…
Thinking Outside the BBox: Unconstrained Generative Object Compositing
Gemma Canet Tarrés, Zhe Lin, Zhifei Zhang +6
Compositing an object into an image involves multiple non-trivial sub-tasks such as object placement and scaling, color/lighting harmonization, viewpoint/geometry adjustment, and s…
WAS: Dataset and Methods for Artistic Text Segmentation
Xudong Xie, Yuzhe Li, Yang Liu +4
Accurate text segmentation results are crucial for text-related generative tasks, such as text image generation, text editing, text removal, and text style transfer. Recently, some…
SwapAnything: Enabling Arbitrary Object Swapping in Personalized Visual Editing
Jing Gu, Nanxuan Zhao, Wei Xiong +7
Effective editing of personal content holds a pivotal role in enabling individuals to express their creativity, weaving captivating narratives within their visual stories, and elev…
IMPRINT: Generative Object Compositing by Learning Identity-Preserving Representation
Yizhi Song, Zhifei Zhang, Zhe Lin +7
Generative object compositing emerges as a promising new avenue for compositional image editing. However, the requirement of object identity preservation poses a significant challe…