Zobrazeno 1 - 10
of 256
pro vyhledávání: '"Heikkilä, Janne"'
This paper introduces GS-Pose, a unified framework for localizing and estimating the 6D pose of novel objects. GS-Pose begins with a set of posed RGB images of a previously unseen object and builds three distinct representations stored in a database.
Externí odkaz:
http://arxiv.org/abs/2403.10683
Point clouds have been a recent interest for ray tracing-based radio channel characterization, as sensors such as RGB-D cameras and laser scanners can be utilized to generate an accurate virtual copy of a physical environment. In this paper, a novel
Externí odkaz:
http://arxiv.org/abs/2403.06648
Ray tracing is a deterministic method that produces propagation paths between a transmitter and a receiver. The simulation accuracy is significantly influenced by the environment details. One way to capture the environment with great precision is the
Externí odkaz:
http://arxiv.org/abs/2402.13747
Despite the impressive performance of recent unbiased Scene Graph Generation (SGG) methods, the current debiasing literature mainly focuses on the long-tailed distribution problem, whereas it overlooks another source of bias, i.e., semantic confusion
Externí odkaz:
http://arxiv.org/abs/2307.05276
Autor:
Otani, Mayu, Togashi, Riku, Sawai, Yu, Ishigami, Ryosuke, Nakashima, Yuta, Rahtu, Esa, Heikkilä, Janne, Satoh, Shin'ichi
Human evaluation is critical for validating the performance of text-to-image generative models, as this highly cognitive process requires deep comprehension of text and images. However, our survey of 37 recent papers reveals that many works rely sole
Externí odkaz:
http://arxiv.org/abs/2304.01816
Acquiring labeled 6D poses from real images is an expensive and time-consuming task. Though massive amounts of synthetic RGB images are easy to obtain, the models trained on them suffer from noticeable performance degradation due to the synthetic-to-
Externí odkaz:
http://arxiv.org/abs/2302.07300
Many computer vision applications require robust and efficient estimation of camera geometry from a minimal number of input data measurements, i.e., solving minimal problems in a RANSAC framework. Minimal problems are usually formulated as complex sy
Externí odkaz:
http://arxiv.org/abs/2301.06443
Various datasets have been proposed for simultaneous localization and mapping (SLAM) and related problems. Existing datasets often include small environments, have incomplete ground truth, or lack important sensor data, such as depth and infrared ima
Externí odkaz:
http://arxiv.org/abs/2301.01057
This paper presents an efficient symmetry-agnostic and correspondence-free framework, referred to as SC6D, for 6D object pose estimation from a single monocular RGB image. SC6D requires neither the 3D CAD model of the object nor any prior knowledge o
Externí odkaz:
http://arxiv.org/abs/2208.02129
Mean Average Precision (mAP) is the primary evaluation measure for object detection. Although object detection has a broad range of applications, mAP evaluates detectors in terms of the performance of ranked instance retrieval. Such the assumption fo
Externí odkaz:
http://arxiv.org/abs/2203.14438