output
20142026
most citedSpoken Language Interaction with Robots: Research Issues and Recommendations, Report from the NSF Future Directions Workshop

113 citations

Showing cs.CVShow all

6 papers · 1 filter

cs.CV2026

Explanatory Interactive Machine Learning for Bias Mitigation in Visual Gender Classification

Nathanya Satriani, Djordje Slijepčević, Markus Schedl +1

Explanatory interactive learning (XIL) enables users to guide model training in machine learning (ML) by providing feedback on the model's explanations, thereby helping it to focus…

cs.CV2025

Bringing Diversity from Diffusion Models to Semantic-Guided Face Asset Generation

Yunxuan Cai, Sitao Xiang, Zongjian Li +2

Digital modeling and reconstruction of human faces serve various applications. However, its availability is often hindered by the requirements of data capturing devices, manual lab…

cs.CV2025★ 4 cited

SplatMAP: Online Dense Monocular SLAM with 3D Gaussian Splatting

Yue Hu, Rong Liu, Meida Chen +2

Achieving high-fidelity 3D reconstruction from monocular video remains challenging due to the inherent limitations of traditional methods like Structure-from-Motion (SfM) and monoc…

cs.CV2020★ 4 cited

Learning Formation of Physically-Based Face Attributes

Ruilong Li, Karl Bladin, Yajie Zhao +8

Based on a combined data set of 4000 high resolution facial scans, we introduce a non-linear morphable face model, capable of producing multifarious face geometry of pore-level res…

cs.CV2018★ 15 cited

Identity Preserving Face Completion for Large Ocular Region Occlusion

Yajie Zhao, Weikai Chen, Jun Xing +5

We present a novel deep learning approach to synthesize complete face images in the presence of large ocular region occlusions. This is motivated by recent surge of VR/AR displays…

cs.CV2014

Relative Facial Action Unit Detection

Mahmoud Khademi, Louis-Philippe Morency

This paper presents a subject-independent facial action unit (AU) detection method by introducing the concept of relative AU detection, for scenarios where the neutral face is not…