Search Results for author: Huaicheng Yan

Found 7 papers, 1 papers with code

Unimodal-driven Distillation in Multimodal Emotion Recognition with Dynamic Fusion

no code implementations31 Mar 2025 Jiagen Li, Rui Yu, Huihao Huang, Huaicheng Yan

Multimodal Emotion Recognition in Conversations (MERC) identifies emotional states across text, audio and video, which is essential for intelligent dialogue systems and opinion analysis.

Knowledge Distillation Mixture-of-Experts +1

Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation

no code implementations17 Sep 2024 Rui Yu, Runkai Zhao, Jiagen Li, Qingsong Zhao, Songhao Zhu, Huaicheng Yan, Meng Wang

The LiDAR-based 3D object detector that strikes a balance between accuracy and speed is crucial for achieving real-time perception in autonomous driving and robotic navigation systems.

3D Object Detection Autonomous Driving +5

Nonlinear Cooperative Output Regulation with Input Delay Compensation

no code implementations8 Sep 2024 Shiqi Zheng, Choon Ki Ahn, Xiaowei Jiang, Huaicheng Yan, Peng Shi

First, a new periodic event-triggered distributed observer, which is based on the fully asynchronous communication data, is proposed to estimate the leader information.

Future Does Matter: Boosting 3D Object Detection with Temporal Motion Estimation in Point Cloud Sequences

no code implementations6 Sep 2024 Rui Yu, Runkai Zhao, Cong Nie, Heng Wang, Huaicheng Yan, Meng Wang

Specifically, Motion-Guided Feature Aggregation (MGFA) is proposed to utilize the object trajectory from previous and future motion states to model spatial-temporal correlations into gaussian heatmap over a driving sequence.

3D Object Detection Motion Estimation +4

Proximal Policy Optimization Learning based Control of Congested Freeway Traffic

no code implementations12 Apr 2022 Shurong Mo, Nailong Wu, Jie Qi, Anqi Pan, Zhiguang Feng, Huaicheng Yan, Yueying Wang

The control gains for the three feedbacks are learned from the interaction between the PPO and the numerical simulator of the traffic system without knowing the system dynamics.

Toward Packet Routing with Fully-distributed Multi-agent Deep Reinforcement Learning

no code implementations9 May 2019 Xinyu You, Xuanjie Li, Yuedong Xu, Hui Feng, Jin Zhao, Huaicheng Yan

Packet routing is one of the fundamental problems in computer networks in which a router determines the next-hop of each packet in the queue to get it as quickly as possible to its destination.

Decision Making Deep Reinforcement Learning +3

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