7 citations · 11 across the 13 of their papers we have counts for
13 papers
Avatar-Forever: Decoupled Parallel Training for High-Quality Real-Time Infinite Avatars
Ruibin Li, Tao Yang, Zhiyuan Ma +3
Existing streaming video systems often rely on sequential, distillation-centered training pipelines to enable few-step long-video generation. However, this paradigm suffers from tw…
DepthMaster: Unified Monocular Depth Estimation for Perspective and Panoramic Images
Pengfei Wang, Shihao Wang, Liyi Chen +3
While monocular depth estimation has achieved significant progress, achieving generalized metric depth estimation for both narrow field-of-view (FoV) perspectives and p…
Memorize When Needed: Decoupled Memory Control for Spatially Consistent Long-Horizon Video Generation
Yanjun Guo, Zhengqiang Zhang, Pengfei Wang +3
Spatially consistent long-horizon video generation aims to maintain temporal and spatial consistency along predefined camera trajectories. Existing methods mostly entangle memory m…
Omni-3DEdit: Generalized Versatile 3D Editing in One-Pass
Chen Liyi, Wang Pengfei, Zhang Guowen +2
Most instruction-driven 3D editing methods rely on 2D models to guide the explicit and iterative optimization of 3D representations. This paradigm, however, suffers from two primar…
One2Scene: Geometric Consistent Explorable 3D Scene Generation from a Single Image
Pengfei Wang, Liyi Chen, Zhiyuan Ma +3
Generating explorable 3D scenes from a single image is a highly challenging problem in 3D vision. Existing methods struggle to support free exploration, often producing severe geom…
RL-RIG: A Generative Spatial Reasoner via Intrinsic Reflection
Tianyu Wang, Zhiyuan Ma, Qian Wang +3
Recent advancements in image generation have achieved impressive results in producing high-quality images. However, existing image generation models still generally struggle with a…
AlignCVC: Aligning Cross-View Consistency for Single-Image-to-3D Generation
Xinyue Liang, Zhiyuan Ma, Lingchen Sun +2
Single-image-to-3D models typically follow a sequential generation and reconstruction workflow. However, intermediate multi-view images synthesized by pre-trained generation models…
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data
Zhiyuan Ma, Xinyue Liang, Rongyuan Wu +3
It is highly desirable to obtain a model that can generate high-quality 3D meshes from text prompts in just seconds. While recent attempts have adapted pre-trained text-to-image di…
Pixel-level and Semantic-level Adjustable Super-resolution: A Dual-LoRA Approach
Lingchen Sun, Rongyuan Wu, Zhiyuan Ma +3
Diffusion prior-based methods have shown impressive results in real-world image super-resolution (SR). However, most existing methods entangle pixel-level and semantic-level SR obj…
Dense Multimodal Alignment for Open-Vocabulary 3D Scene Understanding
Ruihuang Li, Zhengqiang Zhang, Chenhang He +3
Recent vision-language pre-training models have exhibited remarkable generalization ability in zero-shot recognition tasks. Previous open-vocabulary 3D scene understanding methods…
ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillation
Zhiyuan Ma, Yuxiang Wei, Yabin Zhang +3
By leveraging the text-to-image diffusion priors, score distillation can synthesize 3D contents without paired text-3D training data. Instead of spending hours of online optimizati…
One-Step Effective Diffusion Network for Real-World Image Super-Resolution
Rongyuan Wu, Lingchen Sun, Zhiyuan Ma +1
The pre-trained text-to-image diffusion models have been increasingly employed to tackle the real-world image super-resolution (Real-ISR) problem due to their powerful generative i…
Dual Memory Networks: A Versatile Adaptation Approach for Vision-Language Models
Yabin Zhang, Wenjie Zhu, Hui Tang +3
With the emergence of pre-trained vision-language models like CLIP, how to adapt them to various downstream classification tasks has garnered significant attention in recent resear…