23 citations · 26 across the 8 of their papers we have counts for
8 papers
PixelART: Image-to-Layer Decomposition without Latents or Text-to-Image Pretraining
Zelin Jia, Zhao Zhang, Zhicong Tang +2
Image-to-layer decomposition converts a flattened image into editable RGBA layers, enabling element-level editing in design workflows. Existing diffusion-based systems typically ad…
MRT: Masked Region Transformer for Layered Image Generation and Editing at Scale
Zhicong Tang, Zhao Zhang, Jingye Chen +6
Layered image generation and editing is a fundamental capability that enables layer-wise reuse, editing, and composition of generated visual content, analogous to word-level editin…
Incorporating Pre-trained Diffusion Models in Solving the Schrödinger Bridge Problem
Zhicong Tang, Tiankai Hang, Shuyang Gu +2
This paper aims to unify Score-based Generative Models (SGMs), also known as Diffusion models, and the Schrödinger Bridge (SB) problem through three reparameterization techniques:…
ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image Generation
Yifan Pu, Yiming Zhao, Zhicong Tang +14
Multi-layer image generation is a fundamental task that enables users to isolate, select, and edit specific image layers, thereby revolutionizing interactions with generative model…
Diffusion Models without Classifier-free Guidance
Zhicong Tang, Jianmin Bao, Dong Chen +1
This paper presents Model-guidance (MG), a novel objective for training diffusion model that addresses and removes of the commonly used Classifier-free guidance (CFG). Our innovati…
Simplified Diffusion Schrödinger Bridge
Zhicong Tang, Tiankai Hang, Shuyang Gu +2
This paper introduces a novel theoretical simplification of the Diffusion Schrödinger Bridge (DSB) that facilitates its unification with Score-based Generative Models (SGMs), addre…
VolumeDiffusion: Flexible Text-to-3D Generation with Efficient Volumetric Encoder
Zhicong Tang, Shuyang Gu, Chunyu Wang +4
This paper introduces a pioneering 3D volumetric encoder designed for text-to-3D generation. To scale up the training data for the diffusion model, a lightweight network is develop…
Improved Vector Quantized Diffusion Models
Zhicong Tang, Shuyang Gu, Jianmin Bao +2
Vector quantized diffusion (VQ-Diffusion) is a powerful generative model for text-to-image synthesis, but sometimes can still generate low-quality samples or weakly correlated imag…