Tootfinder

i reminded myself of an acronym i learned from a book i bought over 30 years ago
there was an amazing amount of _pnambic_ AI going on in the years before the launch of ChatGPT
i wonder how much of it still exists
eg i know there are two people employed as remote-operator drivers per google “driverless” car

Multistream Network for LiDAR and Camera-based 3D Object Detection in Outdoor Scenes
Muhammad Ibrahim, Naveed Akhtar, Haitian Wang, Saeed Anwar, Ajmal Mian
https://arxiv.org/abs/2507.19304

Multistream Network for LiDAR and Camera-based 3D Object Detection in Outdoor Scenes
Fusion of LiDAR and RGB data has the potential to enhance outdoor 3D object detection accuracy. To address real-world challenges in outdoor 3D object detection, fusion of LiDAR and RGB input has started gaining traction. However, effective integration of these modalities for precise object detection task still remains a largely open problem. To address that, we propose a MultiStream Detection (MuStD) network, that meticulously extracts task-relevant information from both data modalities. The ne…

Malik Nabers injury update: Giants WR says 'my body is gonna turn it on' for Week 1 despite offseason setbacks

https://www.cbssports.com/nfl/news…

To bind or not to bind? Discovering Stable Relationships in Object-centric Processes (Extended Version)
Anjo Seidel, Sarah Winkler, Alessandro Gianola, Marco Montali, Mathias Weske
https://arxiv.org/abs/2508.18231

To bind or not to bind? Discovering Stable Relationships in Object-centric Processes (Extended Version)
Object-centric process mining investigates the intertwined behavior of multiple objects in business processes. From object-centric event logs, object-centric Petri nets (OCPN) can be discovered to replay the behavior of processes accessing different object types. Although they indicate how objects flow through the process and co-occur in events, OCPNs remain underspecified about the relationships of objects. Hence, they are not able to represent synchronization, i.e. executing objects only acco…

Gentle Object Retraction in Dense Clutter Using Multimodal Force Sensing and Imitation Learning
Dane Brouwer, Joshua Citron, Heather Nolte, Jeannette Bohg, Mark Cutkosky
https://arxiv.org/abs/2508.19476

Gentle Object Retraction in Dense Clutter Using Multimodal Force Sensing and Imitation Learning
Dense collections of movable objects are common in everyday spaces -- from cabinets in a home to shelves in a warehouse. Safely retracting objects from such collections is difficult for robots, yet people do it easily, using non-prehensile tactile sensing on the sides and backs of their hands and arms. We investigate the role of such sensing for training robots to gently reach into constrained clutter and extract objects. The available sensing modalities are (1) "eye-in-hand" vision, (2) propri…

Minneapolis Catholic school gunman ID'd as Robin Westman-- while possible manifesto shows psychotic obsession with mass shooters (New York Post)
https://nypost.com/2025/08/27/us-news/minneapolis-catholic-school-gunman-idd-as-robin-westman-while-possible-manifesto-shows-psychotic-obsession-with-mass-shooters/
http://www.memeorandum.com/250827/p105#a250827p105

Enriching Object-Centric Event Data with Process Scopes: A Framework for Aggregation and Analysis
Shahrzad Khayatbashi, Majid Rafiei, Jiayuan Chen, Timotheus Kampik, Gregor Berg, Amin Jalali
https://arxiv.org/abs/2508.18830

Enriching Object-Centric Event Data with Process Scopes: A Framework for Aggregation and Analysis
Object-Centric Process Mining enables the analysis of complex operational behavior by capturing interactions among multiple business objects (e.g., orders, items, deliveries). These interactions are recorded using Object-Centric Event Data (OCED) formats, such as the Object-Centric Event Log (OCEL). However, existing formats lack explicit definitions of process scopes, which restricts analysis to individual processes and limits insights to a low level of granularity. In practice, OCED often spa…

Delightful essay about what is important in social networking, especially with regard to photography https://social.ewenbell.com/objects/85d71187-5187-41ab-827c-ffbcf53bb8ff

Ewen Bell 📸 (@ewen@social.ewenbell.com)
Sharing is caring. Today's video begins by asking "Why do we share photos?" and ends up with 16 minutes of oversharing. Enjoy! #EwenTube #Photography #PhotoVlog Vlog 085 "Does photography have to...

Inference of Human-derived Specifications of Object Placement via Demonstration
Alex Cuellar, Ho Chit Siu, Julie A Shah
https://arxiv.org/abs/2508.19367 https://

Inference of Human-derived Specifications of Object Placement via Demonstration
As robots' manipulation capabilities improve for pick-and-place tasks (e.g., object packing, sorting, and kitting), methods focused on understanding human-acceptable object configurations remain limited expressively with regard to capturing spatial relationships important to humans. To advance robotic understanding of human rules for object arrangement, we introduce positionally-augmented RCC (PARCC), a formal logic framework based on region connection calculus (RCC) for describing the relative…

Foundation Model-Driven Grasping of Unknown Objects via Center of Gravity Estimation
Kang Xiangli, Yage He, Xianwu Gong, Zehan Liu, Yuru Bai
https://arxiv.org/abs/2507.19242 htt…

Foundation Model-Driven Grasping of Unknown Objects via Center of Gravity Estimation
This study presents a grasping method for objects with uneven mass distribution by leveraging diffusion models to localize the center of gravity (CoG) on unknown objects. In robotic grasping, CoG deviation often leads to postural instability, where existing keypoint-based or affordance-driven methods exhibit limitations. We constructed a dataset of 790 images featuring unevenly distributed objects with keypoint annotations for CoG localization. A vision-driven framework based on foundation mode…