collaborators

7 papers

cs.CV2026

EgoPlay: Event-Triggered Video Editing for Egocentric Streams

Jinjie Mai, Gordon Guocheng Qian, Willi Menapace +8

We introduce EgoPlay, an event-triggered video-to-video editor for egocentric streams, obtained by fine-tuning a pretrained V2V diffusion transformer on event-conditioned data buil…

cs.CV2026

MeshLoom: Feed-Forward Non-Rigid Registration of Mesh Sequences

Jianqi Chen, Jiraphon Yenphraphai, Xiangjun Tang +4

We present MeshLoom, a feed-forward registration network that directly reconstructs vertex deformations across mesh sequences. Our approach advances non-rigid registration beyond e…

cs.CV2026

GeoStream: Toward Precise Camera Controlled Streaming Video Generation

Yizhou Zhao, Yifan Wang, Xiaoyuan Wang +11

Accurate interactive camera control is essential for video-based world models, but most existing approaches learn camera motion implicitly, leading to inaccurate control under out-…

cs.CV2026

Helix4D: Complex 4D Mesh Generation

Jiraphon Yenphraphai, Jianqi Chen, Jian Wang +6

Current video-to-4D methods struggle with complex topology changes, transparent materials, thin structures, and inner surfaces. We present Helix4D, a dynamic mesh generation framew…

cs.CV2026

NearID: Identity Representation Learning via Near-identity Distractors

Aleksandar Cvejic, Rameen Abdal, Abdelrahman Eldesokey +2

When evaluating identity-focused tasks such as personalized generation and image editing, existing vision encoders entangle object identity with background context, leading to unre…

cs.CV2026

ArtifactLens: Hundreds of Labels Are Enough for Artifact Detection with VLMs

James Burgess, Rameen Abdal, Dan Stoddart +3

Modern image generators produce strikingly realistic images, where only artifacts like distorted hands or warped objects reveal their synthetic origin. Detecting these artifacts is…

cs.CV2026

Visual Personalization Turing Test

Rameen Abdal, James Burgess, Sergey Tulyakov +1

We introduce the Visual Personalization Turing Test (VPTT), a new paradigm for evaluating contextual visual personalization based on perceptual indistinguishability, rather than id…