Tootfinder

Great research and sloppy work by the Kremlin 😀
"Where's Putin? How The Kremlin Hides His Location With Three Nearly Identical Offices"
https://www.rferl.org/a/kremlin-trickery-putin-offices-secrecy-investigation/33586451.html

Where's Putin? How The Kremlin Hides His Location With Three Nearly Identical Offices
Russian President Vladimir Putin has three nearly identical offices in different parts of the country and the Kremlin has been dishonest about his location many times in recent years, Systema, RFE/RL’s Russian investigative unit, has discovered.

»`Uint8Array.prototype.toHex()`
The toHex() method of Uint8Array instances returns a hex-encoded string based on the data in this Uint8Array object.«
I've only just discovered this and I think it's a cool new feature in JavaScript. I am now surprised when almost all users have up-to-date web browsers in order to use it easily in the frontend WebDev.
🧑‍💻

Uint8Array.prototype.toHex() - JavaScript | MDN
The toHex() method of Uint8Array instances returns a hex-encoded string based on the data in this Uint8Array object.

ooh these bagels have an occlupanid
https://www.horg.com/horg/
haven’t seen one in the wild for ages!

Yesterday at the @… conference, the Brücke-Museum Berlin presented its digitization project on Karl Schmidt-Rottluff’s collection of objects from colonial contexts. All objects have been published on #wikiCommons, allowing everyone to contribute and r…

Two-stream network-driven vision-based tactile sensor for object feature extraction and fusion perception
Muxing Huang, Zibin Chen, Weiliang Xu, Zilan Li, Yuanzhi Zhou, Guoyuan Zhou, Wenjing Chen, Xinming Li
https://arxiv.org/abs/2510.12528

Two-stream network-driven vision-based tactile sensor for object feature extraction and fusion perception
Tactile perception is crucial for embodied intelligent robots to recognize objects. Vision-based tactile sensors extract object physical attributes multidimensionally using high spatial resolution; however, this process generates abundant redundant information. Furthermore, single-dimensional extraction, lacking effective fusion, fails to fully characterize object attributes. These challenges hinder the improvement of recognition accuracy. To address this issue, this study introduces a two-stre…

Beyond 'Templates': Category-Agnostic Object Pose, Size, and Shape Estimation from a Single View
Jinyu Zhang, Haitao Lin, Jiashu Hou, Xiangyang Xue, Yanwei Fu
https://arxiv.org/abs/2510.11687

Beyond 'Templates': Category-Agnostic Object Pose, Size, and Shape Estimation from a Single View
Estimating an object's 6D pose, size, and shape from visual input is a fundamental problem in computer vision, with critical applications in robotic grasping and manipulation. Existing methods either rely on object-specific priors such as CAD models or templates, or suffer from limited generalization across categories due to pose-shape entanglement and multi-stage pipelines. In this work, we propose a unified, category-agnostic framework that simultaneously predicts 6D pose, size, and dense sha…

Raiders offseason idea: Khalil Mack rejoins the Silver and Black https://raiderramble.com/2025/12/14/raiders-offseason-idea-khalil-mack-rejoins-the-silver-and-black/

NV3D: Leveraging Spatial Shape Through Normal Vector-based 3D Object Detection
Krittin Chaowakarn, Paramin Sangwongngam, Nang Htet Htet Aung, Chalie Charoenlarpnopparut
https://arxiv.org/abs/2510.11632

NV3D: Leveraging Spatial Shape Through Normal Vector-based 3D Object Detection
Recent studies in 3D object detection for autonomous vehicles aim to enrich features through the utilization of multi-modal setups or the extraction of local patterns within LiDAR point clouds. However, multi-modal methods face significant challenges in feature alignment, and gaining features locally can be oversimplified for complex 3D object detection tasks. In this paper, we propose a novel model, NV3D, which utilizes local features acquired from voxel neighbors, as normal vectors computed p…

Mask Consistency Regularization in Object Removal
Hua Yuan, Jin Yuan, Yicheng Jiang, Yao Zhang, Xin Geng, Yong Rui
https://arxiv.org/abs/2509.10259 https://

Mask Consistency Regularization in Object Removal
Object removal, a challenging task within image inpainting, involves seamlessly filling the removed region with content that matches the surrounding context. Despite advancements in diffusion models, current methods still face two critical challenges. The first is mask hallucination, where the model generates irrelevant or spurious content inside the masked region, and the second is mask-shape bias, where the model fills the masked area with an object that mimics the mask's shape rather than su…

MMOT: The First Challenging Benchmark for Drone-based Multispectral Multi-Object Tracking
Tianhao Li, Tingfa Xu, Ying Wang, Haolin Qin, Xu Lin, Jianan Li
https://arxiv.org/abs/2510.12565

MMOT: The First Challenging Benchmark for Drone-based Multispectral Multi-Object Tracking
Drone-based multi-object tracking is essential yet highly challenging due to small targets, severe occlusions, and cluttered backgrounds. Existing RGB-based tracking algorithms heavily depend on spatial appearance cues such as color and texture, which often degrade in aerial views, compromising reliability. Multispectral imagery, capturing pixel-level spectral reflectance, provides crucial cues that enhance object discriminability under degraded spatial conditions. However, the lack of dedicate…