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20242026
most citedStereoCrafter: Diffusion-based Generation of Long and High-fidelity Stereoscopic 3D from Monocular Videos

2 citations · 3 across the 18 of their papers we have counts for

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cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 2 cited

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 1 cited

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.…

cs.CV2024

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…