60 citations · 138 across the 10 of their papers we have counts for
7 papers · 1 filter
ALWOD: Active Learning for Weakly-Supervised Object Detection
Yuting Wang, Velibor Ilic, Jiatong Li +2
Object detection (OD), a crucial vision task, remains challenged by the lack of large training datasets with precise object localization labels. In this work, we propose ALWOD, a n…
Graph-based Topology Reasoning for Driving Scenes
Tianyu Li, Li Chen, Huijie Wang +10
Understanding the road genome is essential to realize autonomous driving. This highly intelligent problem contains two aspects - the connection relationship of lanes, and the assig…
D2DF2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation
Yuting Wang, Ricardo Guerrero, Vladimir Pavlovic
Weakly-supervised object detection (WSOD) models attempt to leverage image-level annotations in lieu of accurate but costly-to-obtain object localization labels. This oftentimes le…
Contrastive Masked Autoencoders for Self-Supervised Video Hashing
Yuting Wang, Jinpeng Wang, Bin Chen +2
Self-Supervised Video Hashing (SSVH) models learn to generate short binary representations for videos without ground-truth supervision, facilitating large-scale video retrieval eff…
TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction
Yuting Wang, Hangning Zhou, Zhigang Zhang +10
This technical report presents an effective method for motion prediction in autonomous driving. We develop a Transformer-based method for input encoding and trajectory prediction.…
Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network
Hai X. Pham, Yuting Wang, Vladimir Pavlovic
This paper presents Generative Adversarial Talking Head (GATH), a novel deep generative neural network that enables fully automatic facial expression synthesis of an arbitrary port…
End-to-end Learning for 3D Facial Animation from Raw Waveforms of Speech
Hai X. Pham, Yuting Wang, Vladimir Pavlovic
We present a deep learning framework for real-time speech-driven 3D facial animation from just raw waveforms. Our deep neural network directly maps an input sequence of speech audi…