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20232025
most citedS4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

18 citations · 26 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024★ 3 cited

PRISM: PRogressive dependency maxImization for Scale-invariant image Matching

Xudong Cai, Yongcai Wang, Lun Luo +5

Image matching aims at identifying corresponding points between a pair of images. Currently, detector-free methods have shown impressive performance in challenging scenarios, thank…

cs.CV2024

ModaLink: Unifying Modalities for Efficient Image-to-PointCloud Place Recognition

Weidong Xie, Lun Luo, Nanfei Ye +7

Place recognition is an important task for robots and autonomous cars to localize themselves and close loops in pre-built maps. While single-modal sensor-based methods have shown s…

cs.CV2024

Eliminating Warping Shakes for Unsupervised Online Video Stitching

Lang Nie, Chunyu Lin, Kang Liao +4

In this paper, we retarget video stitching to an emerging issue, named warping shake, when extending image stitching to video stitching. It unveils the temporal instability of warp…

cs.CV2024

Distilling Temporal Knowledge with Masked Feature Reconstruction for 3D Object Detection

Haowen Zheng, Dong Cao, Jintao Xu +4

Striking a balance between precision and efficiency presents a prominent challenge in the bird's-eye-view (BEV) 3D object detection. Although previous camera-based BEV methods achi…

cs.CV2023★ 1 cited

Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications

Junyi Ma, Xieyuanli Chen, Jiawei Huang +6

Understanding how the surrounding environment changes is crucial for performing downstream tasks safely and reliably in autonomous driving applications. Recent occupancy estimation…

cs.CV2023★ 1 cited

WeatherDepth: Curriculum Contrastive Learning for Self-Supervised Depth Estimation under Adverse Weather Conditions

Jiyuan Wang, Chunyu Lin, Lang Nie +4

Depth estimation models have shown promising performance on clear scenes but fail to generalize to adverse weather conditions due to illumination variations, weather particles, etc…