2 citations · 3 across the 18 of their papers we have counts for
21 papers
EditHero: A Benchmark for Long-Horizon Part-Level 3D Editing and Vibe Modeling
Ruihan Yu, Yu-Ju Tsai, Muyao Niu +9
3D editing methods are usually tested on a single edit, yet an asset is built through a long sequence of revisions, each of which must implement the requested change while leaving…
KaiNinja: Extending Native 3D Generators to the Part Level
Ruihan Yu, Lian Fu, Muyao Niu +9
Native 3D generators turn one image into a single mesh. TRELLIS.2 and its peers deliver high-fidelity non-watertight geometry with materials, but the output is one fused object, wh…
Programmable World Model
Zheng-Hui Huang, Guixu Lin, Jiacheng Lin +8
Recent video world models generate increasingly realistic and interactive visual experiences, yet lack reliable mechanisms for maintaining persistent world state and enforcing prog…
WorldSculpt: Generating Compositional Worlds from Grounded Videos
Muyao Niu, Jixuan He, Ruihan Yu +9
We study the problem of generating a compositional 3D representation of a cluttered scene containing hundreds of objects. The goal is to represent the scene as a collection of indi…
Toward Robust and 3D-Aware RGB-NIR Imaging in the Dark
Muyao Niu, Mingze Ma, Yifan Zhan +5
Robust low-light imaging remains challenging for the community. Recent studies have explored fusing Near-Infrared (NIR) with noisy RGB to achieve improved enhancement, yet most met…
Surprise Forcing: What to Remember, When to Skip in Long Video Generation
Shuwei Shi, Zhen Li, Muyao Niu +4
Streaming autoregressive diffusion makes minute-scale video synthesis practical, but its bounded context and fixed denoising schedule allocate resources uniformly across a highly n…
SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation
Xiaolong Zhou, Yifei Liu, Ziyang Gong +8
Multimodal Large Language Models (MLLMs) have made rapid progress in spatial intelligence, yet existing spatial reasoning benchmarks largely assume pristine visual inputs and overl…
Composing Driving Worlds through Disentangled Control for Adversarial Scenario Generation
Yifan Zhan, Zhengqing Chen, Qingjie Wang +7
A major challenge in autonomous driving is the "long tail" of safety-critical edge cases, which often emerge from unusual combinations of common traffic elements. Synthesizing thes…
Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform
Yuning Gong, Yifei Liu, Yifan Zhan +21
Neural rendering, particularly 3D Gaussian Splatting (3DGS), has evolved rapidly and become a key component for building world models. However, existing viewer solutions remain fra…
AniCrafter: Customizing Realistic Human-Centric Animation via Avatar-Background Conditioning in Video Diffusion Models
Muyao Niu, Mingdeng Cao, Yifan Zhan +6
Recent advances in video diffusion models have substantially enhanced character animation techniques. However, existing methods primarily depend on structural conditions, such as D…
Tree-NeRV: A Tree-Structured Neural Representation for Efficient Non-Uniform Video Encoding
Jiancheng Zhao, Yifan Zhan, Qingtian Zhu +5
Implicit Neural Representations for Videos (NeRV) have emerged as a powerful paradigm for video representation, enabling direct mappings from frame indices to video frames. However…
R3-Avatar: Record and Retrieve Temporal Codebook for Reconstructing Photorealistic Human Avatars
Yifan Zhan, Wangze Xu, Qingtian Zhu +6
We present R3-Avatar, incorporating a temporal codebook, to overcome the inability of human avatars to be both animatable and of high-fidelity rendering quality. Existing video-bas…
Adversarial Attacks on Event-Based Pedestrian Detectors: A Physical Approach
Guixu Lin, Muyao Niu, Qingtian Zhu +4
Event cameras, known for their low latency and high dynamic range, show great potential in pedestrian detection applications. However, while recent research has primarily focused o…
Physics-Based Adversarial Attack on Near-Infrared Human Detector for Nighttime Surveillance Camera Systems
Muyao Niu, Zhuoxiao Li, Yifan Zhan +3
Many surveillance cameras switch between daytime and nighttime modes based on illuminance levels. During the day, the camera records ordinary RGB images through an enabled IR-cut f…
Motion-Aware Animatable Gaussian Avatars Deblurring
Muyao Niu, Yifan Zhan, Qingtian Zhu +5
The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely on high-quality, sharp images as…
ToMiE: Towards Explicit Exoskeleton for the Reconstruction of Complicated 3D Human Avatars
Yifan Zhan, Qingtian Zhu, Muyao Niu +6
In this paper, we highlight a critical yet often overlooked factor in most 3D human tasks, namely modeling complicated 3D human with with hand-held objects or loose-fitting clothin…
StereoCrafter: Diffusion-based Generation of Long and High-fidelity Stereoscopic 3D from Monocular Videos
Sijie Zhao, Wenbo Hu, Xiaodong Cun +6
This paper presents a novel framework for converting 2D videos to immersive stereoscopic 3D, addressing the growing demand for 3D content in immersive experience. Leveraging founda…
KFD-NeRF: Rethinking Dynamic NeRF with Kalman Filter
Yifan Zhan, Zhuoxiao Li, Muyao Niu +4
We introduce KFD-NeRF, a novel dynamic neural radiance field integrated with an efficient and high-quality motion reconstruction framework based on Kalman filtering. Our key idea i…
RS-NeRF: Neural Radiance Fields from Rolling Shutter Images
Muyao Niu, Tong Chen, Yifan Zhan +3
Neural Radiance Fields (NeRFs) have become increasingly popular because of their impressive ability for novel view synthesis. However, their effectiveness is hindered by the Rollin…
CV-VAE: A Compatible Video VAE for Latent Generative Video Models
Sijie Zhao, Yong Zhang, Xiaodong Cun +5
Spatio-temporal compression of videos, utilizing networks such as Variational Autoencoders (VAE), plays a crucial role in OpenAI's SORA and numerous other video generative models.…
MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Model
Muyao Niu, Xiaodong Cun, Xintao Wang +3
We present MOFA-Video, an advanced controllable image animation method that generates video from the given image using various additional controllable signals (such as human landma…