1 citations · 1 across the 12 of their papers we have counts for
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MID: A Self-supervised Multimodal Iterative Denoising Framework
Chang Nie, Tianchen Deng, Zhe Liu +1
Data denoising is a persistent challenge across scientific and engineering domains. Real-world data is frequently corrupted by complex, non-linear noise, rendering traditional rule…
DIAL-GS: Dynamic Instance Aware Reconstruction for Label-free Street Scenes with 4D Gaussian Splatting
Chenpeng Su, Wenhua Wu, Chensheng Peng +3
Urban scene reconstruction is critical for autonomous driving, enabling structured 3D representations for data synthesis and closed-loop testing. Supervised approaches rely on cost…
Seeing through Uncertainty: Robust Task-Oriented Optimization in Visual Navigation
Yiyuan Pan, Yunzhe Xu, Zhe Liu +1
Visual navigation is a fundamental problem in embodied AI, yet practical deployments demand long-horizon planning capabilities to address multi-objective tasks. A major bottleneck…
MRASfM: Multi-Camera Reconstruction and Aggregation through Structure-from-Motion in Driving Scenes
Lingfeng Xuan, Chang Nie, Yiqing Xu +3
Structure from Motion (SfM) estimates camera poses and reconstructs point clouds, forming a foundation for various tasks. However, applying SfM to driving scenes captured by multi-…
Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration
Yiyuan Pan, Zhe Liu, Hesheng Wang
Autonomous exploration in complex multi-agent reinforcement learning (MARL) with sparse rewards critically depends on providing agents with effective intrinsic motivation. While ar…
MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep Thinking
Chang Nie, Yiqing Xu, Guangming Wang +3
Moving object segmentation plays a vital role in understanding dynamic visual environments. While existing methods rely on multi-frame image sequences to identify moving objects, s…