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Editorial Material
Computer Science, Hardware & Architecture
Frank Dellaert
COMMUNICATIONS OF THE ACM
(2022)
Article
Chemistry, Analytical
Ignacio Vizzo et al.
Summary: This paper presents a practical approach to volumetric surface reconstruction based on truncated signed distance functions (TSDFs), which is suitable for systems with different environments and sensors. By utilizing the OpenVDB library, an effective 3D map representation is achieved, and a C++ and Python library is provided to solve volumetric mapping problems with TSDFs.
Article
Computer Science, Software Engineering
Thomas Mueller et al.
Summary: The research introduces a versatile new input encoding that allows for a reduction in the cost of training and evaluation by using a multiresolution hash table in neural networks.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Robotics
Michael Helmberger et al.
Summary: Research in SLAM has progressed significantly and is now transitioning from academia to real-world applications. However, this transition poses new challenges in terms of accuracy and robustness. To address these challenges, new datasets with cutting-edge hardware and realistic scenarios are required.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Jingwen Wang et al.
Summary: GO-Surf is a direct feature grid optimization method for accurate and fast surface reconstruction from RGB-D sequences. It models the scene with a learned hierarchical feature voxel grid and optimizes feature vectors to minimize the discrepancy between synthesized and observed RGB/depth values. GO-Surf also introduces a novel SDF gradient regularization term to encourage surface smoothness and hole filling while maintaining high frequency details. It achieves a significant speedup over the most related MLP-based approach while maintaining comparable performance on standard benchmarks.
2022 INTERNATIONAL CONFERENCE ON 3D VISION, 3DV
(2022)
Proceedings Paper
Automation & Control Systems
Yue Pan et al.
Summary: Accurate maps are crucial for autonomous navigation robots, especially in handling large amounts of sensor data. Our proposed Voxfield framework can generate more accurate and complete maps online, with lower computational burden. Through a series of experiments, we demonstrate that our method outperforms existing techniques in map coverage, accuracy, and computational time.
2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Cheng Sun et al.
Summary: The study introduces a super-fast convergence approach for reconstructing the per-scene radiance field from a set of images with high quality in a short training time. This method outperforms traditional NeRF in terms of training time and quality.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Zihan Zhu et al.
Summary: This paper presents NICE-SLAM, a dense SLAM system that incorporates multi-level local information through a hierarchical scene representation. It achieves detailed reconstruction on large indoor scenes and demonstrates competitive results in both mapping and tracking quality.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Konstantinos Rematas et al.
Summary: The goal of this work is to reconstruct 3D models and synthesize novel views using data captured by scanning platforms, with significant improvements achieved through the utilization of lidar data, addressing exposure variation, and leveraging image segmentations. The system outperforms traditional methods and recent neural representations in Street View data.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Sara Fridovich-Keil et al.
Summary: We introduce Plenoxels, a system for photorealistic view synthesis using a sparse 3D grid representation with spherical harmonics. This representation can be optimized without neural components and achieves a two orders of magnitude faster speed compared to Neural Radiance Fields on benchmark tasks while maintaining visual quality.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Edgar Sucar et al.
Summary: For the first time, a multilayer perceptron is used as the sole scene representation in a real-time SLAM system for a handheld RGB-D camera. The network is trained in live operation to build a dense, scene-specific implicit 3D model of occupancy and color, allowing for immediate tracking. The iMAP algorithm achieves real-time SLAM through continual training with dynamic information-guided pixel sampling for speed and efficient geometry representation.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Shuaifeng Zhi et al.
Summary: This study introduces a neural network-based approach that can encode appearance, geometry, and semantics simultaneously, achieving accurate semantic labels with a small amount of in-place annotation data, addressing the issues of sparse and noisy semantic labels.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Ignacio Vizzo et al.
Summary: This paper presents a novel approach for LiDAR odometry and mapping, using Poisson surface reconstruction to compute triangle meshes for improved mapping quality and vehicle pose estimation. Surface reconstruction is done in a sliding window fashion to create accurate local maps that can be combined into a global map, showing more geometric details in the 3D map. Evaluation shows higher geometric accuracies compared to other map representations.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Yiduo Wang et al.
Summary: The research presents an efficient, elastic 3D LiDAR reconstruction framework that addresses challenges in large-scale reconstruction. By introducing new submapping techniques and clustering fusion features, the system demonstrates improved scalability in large environments.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Towaki Takikawa et al.
Summary: The study introduces an efficient neural representation that enables real-time rendering of high-fidelity neural SDFs and achieves state-of-the-art geometry reconstruction quality.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021
(2021)
Article
Engineering, Electrical & Electronic
Yiyuan Pan et al.
Summary: The GEM system proposed in this article generates dense local and global elevation maps, maintains global consistency by updating relative poses between submaps, accelerates local mapping by integrating traversability analysis, and ensures real-time performance through CPU-GPU coordinated processing. Substantial experimental results validate the efficiency and effectiveness of GEM.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Proceedings Paper
Automation & Control Systems
Tilman Kuehner et al.
2020 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
(2020)
Article
Robotics
Emanuele Vespa et al.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2018)
Article
Robotics
Thomas Whelan et al.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2015)
Article
Computer Science, Artificial Intelligence
Armin Hornung et al.