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20232026
most citedInpaint4DNeRF: Promptable Spatio-Temporal NeRF Inpainting with Generative Diffusion Models

2 citations · 6 across the 32 of their papers we have counts for

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27 papers · 1 filter

cs.CV2026

RefRoute: Decoupling Conditioning Cost from References via Compact Residual Conditioning and Spatial Routing

Wanning He, Yuyao Zhang, Yu-Wing Tai

Multi-reference image generation requires preserving the appearance of multiple subjects while composing them into a coherent scene. However, existing diffusion transformers common…

cs.CV2026

Just Align : Aligning Predictions, Not Representations

Yuyao Zhang, Yuwei Hu, Ziyang Mai +1

Representation alignment has become an effective way to accelerate diffusion training, but its benefits do not transfer reliably to pixel-space clean-image prediction. In JiT, we f…

cs.CV2026

When Latents Forget Pixels: Restoring Fidelity in Diffusion Transformer Super-Resolution

Yu Shi, Yuyao Zhang, Yu-wing Tai

Image super-resolution (SR) with large generative models has recently achieved remarkable perceptual quality, yet maintaining fidelity to the LR observation remains challenging. In…

cs.CV2026

IDEAL-Bench: Indoor Dataset and Evaluation suite for Analyzing 3D Layout reasoning

Yuening Cai, Junwei Zhou, Youran Qu +1

Spatial question answering is the dominant paradigm for evaluating spatial intelligence in Vision-Language Models (VLMs), but it leaves a complementary axis of spatial competence u…

cs.CV2026

Beyond MoCap: Scaling Motion Tokenizers with Synthetic Human Motion for Generative Modeling

Yiwen Yan, Wanning He, Yu-Wing Tai

Human motion generation models are fundamentally constrained by the limited diversity of motion capture datasets, which predominantly contain common, repetitive actions and fail to…

cs.CV2026

HierEdit: Region-Aware Hierarchical Diffusion for Efficient High-Resolution Editing

Yuyao Zhang, Alexander Huang-Menders, Yu-Wing Tai

High-resolution image editing is essential for professional and creative applications, yet existing multimodal diffusion-based editors remain computationally inefficient and constr…

cs.CV2026

AtlasVid: Efficient Ultra-High-Resolution Long Video Generation via Decoupled Global-Local Modeling

Ziyang Mai, Yuyao Zhang, Yu-Wing Tai

Recent diffusion-based video generators have achieved remarkable visual fidelity and prompt controllability, yet scaling them to ultra-high-resolution (UHR) long videos remains pro…

cs.CV2026

CoT-Seg: Rethinking Segmentation with Chain-of-Thought Reasoning and Self-Correction

Shiu-hong Kao, Chak Ho Huang, Huaiqian Liu +2

Existing works of reasoning segmentation often fall short in complex cases, particularly when addressing complicated queries and out-of-domain images. Inspired by the chain-of-thou…

cs.CV2025

Trace Anything: Representing Any Video in 4D via Trajectory Fields

Xinhang Liu, Yuxi Xiao, Donny Y. Chen +4

Effective spatio-temporal representation is fundamental to modeling, understanding, and predicting dynamics in videos. The atomic unit of a video, the pixel, traces a continuous 3D…

cs.CV2025

SmartAvatar: Text- and Image-Guided Human Avatar Generation with VLM AI Agents

Alexander Huang-Menders, Xinhang Liu, Andy Xu +3

SmartAvatar is a vision-language-agent-driven framework for generating fully rigged, animation-ready 3D human avatars from a single photo or textual prompt. While diffusion-based m…

cs.CV2025

Agentic 3D Scene Generation with Spatially Contextualized VLMs

Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang

Despite recent advances in multimodal content generation enabled by vision-language models (VLMs), their ability to reason about and generate structured 3D scenes remains largely u…

cs.CV2025★ 1 cited

CoT-RVS: Zero-Shot Chain-of-Thought Reasoning Segmentation for Videos

Shiu-hong Kao, Yu-Wing Tai, Chi-Keung Tang

Reasoning Video Object Segmentation is a challenging task, aiming at generating a mask sequence from an input video given a complex and implicit text query. While existing works fi…

cs.CV2025

Multimodal Generation of Animatable 3D Human Models with AvatarForge

Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang

We introduce AvatarForge, a framework for generating animatable 3D human avatars from text or image inputs using AI-driven procedural generation. While diffusion-based methods have…

cs.CV2025

Think Before You Segment: High-Quality Reasoning Segmentation with GPT Chain of Thoughts

Shiu-hong Kao, Yu-Wing Tai, Chi-Keung Tang

Reasoning segmentation is a challenging vision-language task that aims to output the segmentation mask with respect to a complex, implicit, and even non-visual query text. Previous…

cs.CV2025

WorldCraft: Photo-Realistic 3D World Creation and Customization via LLM Agents

Xinhang Liu, Chi-Keung Tang, Yu-Wing Tai

Constructing photorealistic virtual worlds has applications across various fields, but it often requires the extensive labor of highly trained professionals to operate conventional…

cs.CV2025

UVRM: A Scalable 3D Reconstruction Model from Unposed Videos

Shiu-hong Kao, Xiao Li, Jinglu Wang +4

Large Reconstruction Models (LRMs) have recently become a popular method for creating 3D foundational models. Training 3D reconstruction models with 2D visual data traditionally re…

cs.CV2024

ChatCam: Empowering Camera Control through Conversational AI

Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang

Cinematographers adeptly capture the essence of the world, crafting compelling visual narratives through intricate camera movements. Witnessing the strides made by large language m…

cs.CV2024

VP-LLM: Text-Driven 3D Volume Completion with Large Language Models through Patchification

Jianmeng Liu, Yichen Liu, Yuyao Zhang +3

Recent conditional 3D completion works have mainly relied on CLIP or BERT to encode textual information, which cannot support complex instruction. Meanwhile, large language models…

cs.CV2024

Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-aware Spatio-Temporal Sampling

Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang +3

Extensions of Neural Radiance Fields (NeRFs) to model dynamic scenes have enabled their near photo-realistic, free-viewpoint rendering. Although these methods have shown some poten…

cs.CV2024★ 1 cited

Motion-Agent: A Conversational Framework for Human Motion Generation with LLMs

Qi Wu, Yubo Zhao, Yifan Wang +3

While previous approaches to 3D human motion generation have achieved notable success, they often rely on extensive training and are limited to specific tasks. To address these cha…

cs.CV2024

FED-NeRF: Achieve High 3D Consistency and Temporal Coherence for Face Video Editing on Dynamic NeRF

Hao Zhang, Yu-Wing Tai, Chi-Keung Tang

The success of the GAN-NeRF structure has enabled face editing on NeRF to maintain 3D view consistency. However, achieving simultaneously multi-view consistency and temporal cohere…

cs.CV2023★ 2 cited

Inpaint4DNeRF: Promptable Spatio-Temporal NeRF Inpainting with Generative Diffusion Models

Han Jiang, Haosen Sun, Ruoxuan Li +2

Current Neural Radiance Fields (NeRF) can generate photorealistic novel views. For editing 3D scenes represented by NeRF, with the advent of generative models, this paper proposes…

cs.CV2023

Prompt2NeRF-PIL: Fast NeRF Generation via Pretrained Implicit Latent

Jianmeng Liu, Yuyao Zhang, Zeyuan Meng +2

This paper explores promptable NeRF generation (e.g., text prompt or single image prompt) for direct conditioning and fast generation of NeRF parameters for the underlying 3D scene…

cs.CV2023★ 1 cited

Stable Segment Anything Model

Qi Fan, Xin Tao, Lei Ke +6

The Segment Anything Model (SAM) achieves remarkable promptable segmentation given high-quality prompts which, however, often require good skills to specify. To make SAM robust to…