27 citations · 27 across the 11 of their papers we have counts for
7 papers · 1 filter
GLoD-LVSM: Learning Geometry-Grounded Continuous-LoD Scene Representations for Large View Synthesis Models
Weikai Lin, Nicholas Milef, Carl S Marshall +3
Large view synthesis models (LVSMs) reconstruct scenes from sparse views and render novel views quickly, but they incur unnecessary storage and rendering costs due to token redunda…
GazeFlow: From Human Gaze Behavior to Generative Egocentric Gaze Prediction
Sheng Zhao, Weikai Lin, Yuhao Zhu
Egocentric gaze prediction enables many downstream applications but remains challenging, as human gaze is inherently stochastic. This stochasticity is constrained by structured tem…
Multidimensional Observer Model and Perceptual Dimensions of Human Image Quality Assessment
Sheng Zhao, Weikai Lin, Yuhao Zhu
Judging image quality is not only ecologically relevant to everyday human tasks, but also underpins many machine vision tasks such as image generation. This paper proposes a framew…
ControlGS: Conditioning Neural Gaussians for Downstream-Processing-Aware XR Rendering
Weikai Lin, Junjie Zhao, Carl Marshall +2
Extended Reality (XR) users do not directly perceive the output of a rendering engine. Instead, rendered images pass through a post-processing pipeline and the physical display-opt…
MetaSapiens v2: Advancing Real-Time Foveated Neural Rendering via Foveation-Aware Pruning and Stereo Warping
Weikai Lin, Yu Feng
Point-Based Neural Rendering (PBNR) is emerging as a promising class of rendering techniques, which are permeating all aspects of society, driven by a growing demand for real-time,…
LowPowAR: Power-Constrained Tone Mapping for Augmented Reality
Weikai Lin, Sheng Zhao, Ian Ross +3
Everyday-wearable Augmented Reality (AR) glasses must meet strict power limits, making displays a key target for optimization. We cast display power optimization as a power-constra…
SafeDream: Safety World Model for Proactive Early Jailbreak Detection
Bo Yan, Weikai Lin, Yada Zhu +1
Multi-turn jailbreak attacks progressively erode LLM safety alignment across seemingly innocuous conversation turns, achieving success rates exceeding 90% against state-of-the-art…