7 citations · 18 across the 22 of their papers we have counts for
20 papers · 1 filter
LayerRecall: A State-Conditioned Memory Router for Long-Horizon Consistency in Video Generation
Yixuan Ding, Jiahao Kong, Wei Huang +2
Autoregressive video diffusion enables scalable long-video generation by producing chunks from a bounded recent context. While recency-based caching preserves local continuity, it…
Restore3D: Breathing Life into Broken Objects with Shape and Texture Restoration
Xiaolong Shen, Zongxin Yang, Yi Yang
Restoring incomplete or damaged 3D objects is crucial for cultural heritage preservation, occluded object reconstruction, and artistic design. Existing methods primarily focus on g…
MetaPoint: Unlocking Precise Spatial Control in Agentic Visual Generation
Dewei Zhou, Xinyu Huang, Xun Wang +6
Generative visual models fundamentally struggle with precise spatial control. This arises from a core disconnect: models can process textual descriptions of space but cannot direct…
RefineAnything: Multimodal Region-Specific Refinement for Perfect Local Details
Dewei Zhou, You Li, Zongxin Yang +1
We introduce region-specific image refinement as a dedicated problem setting: given an input image and a user-specified region (e.g., a scribble mask or a bounding box), the goal i…
TRACE: High-Fidelity 3D Scene Editing via Tangible Reconstruction and Geometry-Aligned Contextual Video Masking
Jiyuan Hu, Zechuan Zhang, Zongxin Yang +1
Existing 3D Gaussian Splatting (3DGS) editing methods primarily focus on appearance modification and often struggle to support flexible geometry editing while preserving structural…
Stroke3D: Lifting 2D strokes into rigged 3D model via latent diffusion models
Ruisi Zhao, Haoren Zheng, Zongxin Yang +2
Rigged 3D assets are fundamental to 3D deformation and animation. However, existing 3D generation methods face challenges in generating animatable geometry, while rigging technique…
Are Image-to-Video Models Good Zero-Shot Image Editors?
Zechuan Zhang, Zhenyuan Chen, Zongxin Yang +1
Large-scale video diffusion models show strong world simulation and temporal reasoning abilities, but their use as zero-shot image editors remains underexplored. We introduce IF-Ed…
BideDPO: Conditional Image Generation with Simultaneous Text and Condition Alignment
Dewei Zhou, Mingwei Li, Zongxin Yang +5
Conditional image generation enhances text-to-image synthesis with structural, spatial, or stylistic priors, but current methods face challenges in handling conflicts between sourc…
DreamRenderer: Taming Multi-Instance Attribute Control in Large-Scale Text-to-Image Models
Dewei Zhou, Mingwei Li, Zongxin Yang +1
Image-conditioned generation methods, such as depth- and canny-conditioned approaches, have demonstrated remarkable abilities for precise image synthesis. However, existing models…
In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer
Zechuan Zhang, Ji Xie, Yu Lu +2
Instruction-based image editing enables precise modifications via natural language prompts, but existing methods face a precision-efficiency tradeoff: fine-tuning demands massive d…
3D Object Manipulation in a Single Image using Generative Models
Ruisi Zhao, Zechuan Zhang, Zongxin Yang +1
Object manipulation in images aims to not only edit the object's presentation but also gift objects with motion. Previous methods encountered challenges in concurrently handling st…
3DIS-FLUX: simple and efficient multi-instance generation with DiT rendering
Dewei Zhou, Ji Xie, Zongxin Yang +1
The growing demand for controllable outputs in text-to-image generation has driven significant advancements in multi-instance generation (MIG), enabling users to define both instan…
3DIS: Depth-Driven Decoupled Instance Synthesis for Text-to-Image Generation
Dewei Zhou, Ji Xie, Zongxin Yang +1
The increasing demand for controllable outputs in text-to-image generation has spurred advancements in multi-instance generation (MIG), allowing users to define both instance layou…
MIGC++: Advanced Multi-Instance Generation Controller for Image Synthesis
Dewei Zhou, You Li, Fan Ma +2
We introduce the Multi-Instance Generation (MIG) task, which focuses on generating multiple instances within a single image, each accurately placed at predefined positions with att…
MIGC: Multi-Instance Generation Controller for Text-to-Image Synthesis
Dewei Zhou, You Li, Fan Ma +2
We present a Multi-Instance Generation (MIG) task, simultaneously generating multiple instances with diverse controls in one image. Given a set of predefined coordinates and their…
DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)
Zongxin Yang, Guikun Chen, Xiaodi Li +2
Recent LLM-driven visual agents mainly focus on solving image-based tasks, which limits their ability to understand dynamic scenes, making it far from real-life applications like g…
GD^2-NeRF: Generative Detail Compensation via GAN and Diffusion for One-shot Generalizable Neural Radiance Fields
Xiao Pan, Zongxin Yang, Shuai Bai +1
In this paper, we focus on the One-shot Novel View Synthesis (O-NVS) task which targets synthesizing photo-realistic novel views given only one reference image per scene. Previous…
SEEAvatar: Photorealistic Text-to-3D Avatar Generation with Constrained Geometry and Appearance
Yuanyou Xu, Zongxin Yang, Yi Yang
Powered by large-scale text-to-image generation models, text-to-3D avatar generation has made promising progress. However, most methods fail to produce photorealistic results, limi…
Human101: Training 100+FPS Human Gaussians in 100s from 1 View
Mingwei Li, Jiachen Tao, Zongxin Yang +1
Reconstructing the human body from single-view videos plays a pivotal role in the virtual reality domain. One prevalent application scenario necessitates the rapid reconstruction o…
SIFU: Side-view Conditioned Implicit Function for Real-world Usable Clothed Human Reconstruction
Zechuan Zhang, Zongxin Yang, Yi Yang
Creating high-quality 3D models of clothed humans from single images for real-world applications is crucial. Despite recent advancements, accurately reconstructing humans in comple…