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20212026
most citedToken Prediction as Implicit Classification to Identify LLM-Generated Text

20 citations · 61 across the 32 of their papers we have counts for

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12 papers · 1 filter

cs.CV2026

RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring

Renbiao Jin, Mingxin Yang, Yutian Chen +8

Real-world video deblurring remains challenging due to diverse motion patterns, complex degradations, and the scarcity of realistic training data, yet robust restoration is critica…

cs.CV2026

HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System

Tianshuo Yang, Guanyu Chen, Yutian Chen +8

While end-to-end Vision-Language-Action (VLA) models offer a promising paradigm for robotic manipulation, fine-tuning them on narrow control data often compromises the profound rea…

cs.CV2026

AsyncEvGS: Asynchronous Event-Assisted Gaussian Splatting for Handheld Motion-Blurred Scenes

Jun Dai, Renbiao Jin, Bo Xu +5

3D reconstruction methods such as 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) achieve impressive photorealism but fail when input images suffer from severe motio…

cs.CV2026

AnyRecon: Arbitrary-View 3D Reconstruction with Video Diffusion Model

Yutian Chen, Shi Guo, Renbiao Jin +7

Sparse-view 3D reconstruction is essential for modeling scenes from casual captures, but remain challenging for non-generative reconstruction. Existing diffusion-based approaches m…

cs.CV2026

Less Gaussians, Texture More: 4K Feed-Forward Textured Splatting

Yixing Lao, Xuyang Bai, Xiaoyang Wu +7

Existing feed-forward 3D Gaussian Splatting methods predict pixel-aligned primitives, leading to a quadratic growth in primitive count as resolution increases. This fundamentally l…

cs.CV2025

Co-Me: Confidence-Guided Token Merging for Visual Geometric Transformers

Yutian Chen, Yuheng Qiu, Ruogu Li +4

We propose Confidence-Guided Token Merging (Co-Me), an acceleration mechanism for visual geometric transformers without retraining or finetuning the base model. Co-Me distilled a l…

cs.CV2025

Virtual Community: An Open World for Humans, Robots, and Society

Qinhong Zhou, Hongxin Zhang, Xiangye Lin +16

The rapid progress in AI and Robotics may lead to a profound societal transformation, as humans and robots begin to coexist within shared communities, introducing both opportunitie…

cs.CV2025

4DSloMo: 4D Reconstruction for High Speed Scene with Asynchronous Capture

Yutian Chen, Shi Guo, Tianshuo Yang +4

Reconstructing fast-dynamic scenes from multi-view videos is crucial for high-speed motion analysis and realistic 4D reconstruction. However, the majority of 4D capture systems are…

cs.CV2025

UFM: A Simple Path towards Unified Dense Correspondence with Flow

Yuchen Zhang, Nikhil Keetha, Chenwei Lyu +9

Dense image correspondence is central to many applications, such as visual odometry, 3D reconstruction, object association, and re-identification. Historically, dense correspondenc…

cs.CV2024

Event-assisted 12-stop HDR Imaging of Dynamic Scene

Shi Guo, Zixuan Chen, Ziran Zhang +3

High dynamic range (HDR) imaging is a crucial task in computational photography, which captures details across diverse lighting conditions. Traditional HDR fusion methods face limi…

cs.CV2024

TRecViT: A Recurrent Video Transformer

Viorica Pătrăucean, Xu Owen He, Joseph Heyward +10

We propose a novel block for \emph{causal} video modelling. It relies on a time-space-channel factorisation with dedicated blocks for each dimension: gated linear recurrent units (…

cs.CV2024

Event-Based Motion Magnification

Yutian Chen, Shi Guo, Fangzheng Yu +3

Detecting and magnifying imperceptible high-frequency motions in real-world scenarios has substantial implications for industrial and medical applications. These motions are charac…