Zobrazeno 1 - 10
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pro vyhledávání: '"Fua P"'
Visual object counting is a fundamental computer vision task underpinning numerous real-world applications, from cell counting in biomedicine to traffic and wildlife monitoring. However, existing methods struggle to handle the challenge of stacked 3D
Externí odkaz:
http://arxiv.org/abs/2411.19149
Tracking-by-detection has become the de facto standard approach to people tracking. To increase robustness, some approaches incorporate re-identification using appearance models and regressing motion offset, which requires costly identity annotations
Externí odkaz:
http://arxiv.org/abs/2411.16466
Autor:
Durasov, Nikita, Mahmood, Rafid, Choi, Jiwoong, Law, Marc T., Lucas, James, Fua, Pascal, Alvarez, Jose M.
3D object detection is an essential task for computer vision applications in autonomous vehicles and robotics. However, models often struggle to quantify detection reliability, leading to poor performance on unfamiliar scenes. We introduce a framewor
Externí odkaz:
http://arxiv.org/abs/2410.23910
Unsigned Distance Functions (UDFs) can be used to represent non-watertight surfaces in a deep learning framework. However, UDFs tend to be brittle and difficult to learn, in part because the surface is located exactly where the UDF is non-differentia
Externí odkaz:
http://arxiv.org/abs/2410.22422
This paper introduces Idempotent Test-Time Training (IT$^3$), a novel approach to addressing the challenge of distribution shift. While supervised-learning methods assume matching train and test distributions, this is rarely the case for machine lear
Externí odkaz:
http://arxiv.org/abs/2410.04201
Implicit neural representations map a shape-specific latent code and a 3D coordinate to its corresponding signed distance (SDF) value. However, this approach only offers a single level of detail. Emulating low levels of detail can be achieved with sh
Externí odkaz:
http://arxiv.org/abs/2409.06231
Neural Radiance Fields (NeRFs) have become a powerful tool for modeling 3D scenes from multiple images. However, NeRFs remain difficult to segment into semantically meaningful regions. Previous approaches to 3D segmentation of NeRFs either require us
Externí odkaz:
http://arxiv.org/abs/2408.09928
Extracting surfaces from Signed Distance Fields (SDFs) can be accomplished using traditional algorithms, such as Marching Cubes. However, since they rely on sign flips across the surface, these algorithms cannot be used directly on Unsigned Distance
Externí odkaz:
http://arxiv.org/abs/2407.18381
Autor:
Gwizdała, Jakub, Oner, Doruk, Roy, Soumava Kumar, Shah, Mian Akbar, Eberhard, Ad, Egorov, Ivan, Krüsi, Philipp, Yakushev, Grigory, Fua, Pascal
Power lines are dangerous for low-flying aircraft, especially in low-visibility conditions. Thus, a vision-based system able to analyze the aircraft's surroundings and to provide the pilots with a "second pair of eyes" can contribute to enhancing the
Externí odkaz:
http://arxiv.org/abs/2407.14352
Autor:
Fares, Samar, Ziu, Klea, Aremu, Toluwani, Durasov, Nikita, Takáč, Martin, Fua, Pascal, Nandakumar, Karthik, Laptev, Ivan
Vision-Language Models (VLMs) are becoming increasingly vulnerable to adversarial attacks as various novel attack strategies are being proposed against these models. While existing defenses excel in unimodal contexts, they currently fall short in saf
Externí odkaz:
http://arxiv.org/abs/2406.09250