activity
20172023
most citedMISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation

60 citations · 138 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2023

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…

cs.IR2023★ 60 cited

MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation

Jinpeng Wang, Ziyun Zeng, Yunxiao Wang +7

The goal of sequential recommendation (SR) is to predict a user's potential interested items based on her/his historical interaction sequences. Most existing sequential recommender…

cs.CV2023

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…

cs.CV2022

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…

cs.CV2022★ 2 cited

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…

cs.CV2022★ 8 cited

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.…