Zobrazeno 1 - 10
of 181
pro vyhledávání: '"Rahtu, Esa"'
Recent advancements in monocular neural depth estimation, particularly those achieved by the UniDepth network, have prompted the investigation of integrating UniDepth within a Gaussian splatting framework for monocular SLAM.This study presents UDGS-S
Externí odkaz:
http://arxiv.org/abs/2409.00362
Autor:
Turkulainen, Matias, Ren, Xuqian, Melekhov, Iaroslav, Seiskari, Otto, Rahtu, Esa, Kannala, Juho
High-fidelity 3D reconstruction of common indoor scenes is crucial for VR and AR applications. 3D Gaussian splatting, a novel differentiable rendering technique, has achieved state-of-the-art novel view synthesis results with high rendering speeds an
Externí odkaz:
http://arxiv.org/abs/2403.17822
Autor:
Seiskari, Otto, Ylilammi, Jerry, Kaatrasalo, Valtteri, Rantalankila, Pekka, Turkulainen, Matias, Kannala, Juho, Rahtu, Esa, Solin, Arno
High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera motion and
Externí odkaz:
http://arxiv.org/abs/2403.13327
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
Our objective is audio-visual synchronization with a focus on 'in-the-wild' videos, such as those on YouTube, where synchronization cues can be sparse. Our contributions include a novel audio-visual synchronization model, and training that decouples
Externí odkaz:
http://arxiv.org/abs/2401.16423
Autor:
Ahonen, Jukka I., Le, Nam, Zhang, Honglei, Hallapuro, Antti, Cricri, Francesco, Tavakoli, Hamed Rezazadegan, Hannuksela, Miska M., Rahtu, Esa
The recent progress in artificial intelligence has led to an ever-increasing usage of images and videos by machine analysis algorithms, mainly neural networks. Nonetheless, compression, storage and transmission of media have traditionally been design
Externí odkaz:
http://arxiv.org/abs/2401.10761
Autor:
Le, Nam, Zhang, Honglei, Cricri, Francesco, Youvalari, Ramin G., Tavakoli, Hamed Rezazadegan, Aksu, Emre, Hannuksela, Miska M., Rahtu, Esa
Publikováno v:
IEEE International Conference on Image Processing (ICIP), Bordeaux, France, 2022, pp. 3411-3415
Image coding for machines (ICM) aims at reducing the bitrate required to represent an image while minimizing the drop in machine vision analysis accuracy. In many use cases, such as surveillance, it is also important that the visual quality is not dr
Externí odkaz:
http://arxiv.org/abs/2401.10732
Metaverse technologies demand accurate, real-time, and immersive modeling on consumer-grade hardware for both non-human perception (e.g., drone/robot/autonomous car navigation) and immersive technologies like AR/VR, requiring both structural accuracy
Externí odkaz:
http://arxiv.org/abs/2311.02778
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
While the availability of large and diverse datasets has contributed to significant breakthroughs in autonomous driving and indoor applications, forestry applications are still lagging behind and new forest datasets would most certainly contribute to
Externí odkaz:
http://arxiv.org/abs/2304.00793