ChatStitch: Visualizing Through Structures via Surround-View Unsupervised Deep Image Stitching with Collaborative LLM-Agents
Surround-view perception has garnered significant attention for its ability to enhance the perception capabilities of autonomous driving vehicles through the exchange of information with surrounding cameras. However, existing surround-view perception systems are limited by inefficiencies in unidirectional interaction pattern with human and distortions in overlapping regions exponentially propagating into non-overlapping areas. To address these challenges, this paper introduces ChatStitch, a surround-view human-machine co-perception system capable of unveiling obscured blind spot information through natural language commands integrated with external digital assets. To dismantle the unidirectional interaction bottleneck, ChatStitch implements a cognitively grounded closed-loop interaction multi-agent framework based on Large Language Models. To suppress distortion propagation across overlapping boundaries, ChatStitch proposes SV-UDIS, a surround-view unsupervised deep image stitching method under the non-global-overlapping condition. We conducted extensive experiments on the UDIS-D, MCOV-SLAM open datasets, and our real-world dataset. Specifically, our SV-UDIS method achieves state-of-the-art performance on the UDIS-D dataset for 3, 4, and 5 image stitching tasks, with PSNR improvements of 9\%, 17\%, and 21\%, and SSIM improvements of 8\%, 18\%, and 26\%, respectively.
Code (0)
등록된 구현이 없습니다.
Tasks
Autonomous DrivingImage StitchingSSIMMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
GAPNet: Granularity Attention Network with Anatomy-Prior-Constraint for Carotid Artery Segmentation
Atherosclerosis is a chronic, progressive disease that primarily affects the arterial walls. It is one of the major causes of cardiovascular disease. Magnetic Resonance (MR) black-blood vessel wall imaging (BB-VWI) offer…
AnatomyVisualizing Classification Structure of Large-Scale Classifiers
We propose a measure to compute class similarity in large-scale classification based on prediction scores. Such measure has not been formally pro-posed in the literature. We show how visualizing the class similarity matr…
ClassificationGeneral ClassificationVisualizing Uncertainty in Image Guided Surgery a Review
During tumor resection surgery, surgeons rely on neuronavigation to locate tumors and other critical structures in the brain. Most neuronavigation is based on preoperative images, such as MRI and ultrasound, to navigate …
NavigateAerial Manipulation: Contact, Medium Coupling, and the Geometry of Readiness
Aerial robots are increasingly moving from remote observation toward physical interaction with objects, surfaces, structures, loads, and surrounding flows. This review argues that aerial manipulation cannot be understood…
Visualizing Latent Phase Structures in Locomotion Policies: A Multi-Environment Study with Temporal Feature Extension
Deep reinforcement learning (DRL) has been shown to achieve high performance on locomotion control tasks in MuJoCo benchmarks such as HalfCheetah, Ant, and Walker2D. However, visualizing the motion structures internally …
Reinforcement Learning