33 citations · 40 across the 6 of their papers we have counts for
8 papers · 1 filter
ProS: Facial Omni-Representation Learning via Prototype-based Self-Distillation
Xing Di, Yiyu Zheng, Xiaoming Liu +1
This paper presents a novel approach, called Prototype-based Self-Distillation (ProS), for unsupervised face representation learning. The existing supervised methods heavily rely o…
Unsupervised Temporal Video Grounding with Deep Semantic Clustering
Daizong Liu, Xiaoye Qu, Yinzhen Wang +5
Temporal video grounding (TVG) aims to localize a target segment in a video according to a given sentence query. Though respectable works have made decent achievements in this task…
Memory-Guided Semantic Learning Network for Temporal Sentence Grounding
Daizong Liu, Xiaoye Qu, Xing Di +3
Temporal sentence grounding (TSG) is crucial and fundamental for video understanding. Although the existing methods train well-designed deep networks with a large amount of data, w…
A Large-Scale, Time-Synchronized Visible and Thermal Face Dataset
Domenick Poster, Matthew Thielke, Robert Nguyen +8
Thermal face imagery, which captures the naturally emitted heat from the face, is limited in availability compared to face imagery in the visible spectrum. To help address this sca…
Multi-Scale Thermal to Visible Face Verification via Attribute Guided Synthesis
Xing Di, Benjamin S. Riggan, Shuowen Hu +2
Thermal-to-visible face verification is a challenging problem due to the large domain discrepancy between the modalities. Existing approaches either attempt to synthesize visible f…
Facial Synthesis from Visual Attributes via Sketch using Multi-Scale Generators
Xing Di, Vishal M. Patel
Automatic synthesis of faces from visual attributes is an important problem in computer vision and has wide applications in law enforcement and entertainment. With the advent of de…