output
20162025
most citedDeep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

256 citations

34 papers

cs.CV2025★ 6 cited

Source-Free Object Detection with Detection Transformer

Huizai Yao, Sicheng Zhao, Shuo Lu +7

Source-Free Object Detection (SFOD) enables knowledge transfer from a source domain to an unsupervised target domain for object detection without access to source data. Most existi…

cs.CV2024★ 4 cited

PanoSSC: Exploring Monocular Panoptic 3D Scene Reconstruction for Autonomous Driving

Yining Shi, Jiusi Li, Kun Jiang +4

Vision-centric occupancy networks, which represent the surrounding environment with uniform voxels with semantics, have become a new trend for safe driving of camera-only autonomou…

cs.LG2023★ 13 cited

A Data-driven Region Generation Framework for Spatiotemporal Transportation Service Management

Liyue Chen, Jiangyi Fang, Zhe Yu +3

MAUP (modifiable areal unit problem) is a fundamental problem for spatial data management and analysis. As an instantiation of MAUP in online transportation platforms, region gener…

cs.LG2023★ 53 cited

SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization

Dongcheng Zou, Hao Peng, Xiang Huang +5

Graph Neural Networks (GNNs) are de facto solutions to structural data learning. However, it is susceptible to low-quality and unreliable structure, which has been a norm rather th…

cs.CV2021★ 3 cited

Human Pose Transfer with Augmented Disentangled Feature Consistency

Kun Wu, Chengxiang Yin, Zhengping Che +4

Deep generative models have made great progress in synthesizing images with arbitrary human poses and transferring poses of one person to others. Though many different methods have…

cs.LG2021★ 1 cited

A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Xiaocheng Tang, Zhiwei Qin, Fan Zhang +5

Recent works on ride-sharing order dispatching have highlighted the importance of taking into account both the spatial and temporal dynamics in the dispatching process for improvin…