Tootfinder

Urban Solitude III 🈳
城市孤独 III 🈳
📷 Pentax MX
🎞️Fujifilm Neopan SS, expired 1995
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

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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…

Pig unions are a unifying structure of America's Freikorps. Just as the dismantling of the Wehrmacht left a whole lot of trained thugs with nothing to do in Germany, our falling crime rates have left cops in a similar position of idleness, except that they mostly still have jobs where they can create their own work. https://

Jess👾 (@JessTheUnstill@infosec.exchange)
Attached: 1 image "Head of Police Union Said" ... Okay I'm just gonna stop you right there. If a police union head said police officers are human beings, I'd start stockpiling wooden stakes, garlic, and holy water. Those motherfuckers make Fox News look trustworthy.

Neural network-based singularity detection and applications
Nadiia Derevianko, Ioannis G. Kevrekidis, Felix Dietrich
https://arxiv.org/abs/2509.10110 https://

Neural network-based singularity detection and applications
We present a method for constructing a special type of shallow neural network that learns univariate meromorphic functions with pole-type singularities. Our method is based on using a finite set of Laurent coefficients as input information, which we compute by FFT, employing values of the investigated function on some contour $Γ$ in the complex plane. The primary components of our methodology are the following: (1) the adaptive construction of rational polynomial activation functions, (2) a no…

MagicMirror: A Large-Scale Dataset and Benchmark for Fine-Grained Artifacts Assessment in Text-to-Image Generation
Jia Wang, Jie Hu, Xiaoqi Ma, Hanghang Ma, Yanbing Zeng, Xiaoming Wei
https://arxiv.org/abs/2509.10260

MagicMirror: A Large-Scale Dataset and Benchmark for Fine-Grained Artifacts Assessment in Text-to-Image Generation
Text-to-image (T2I) generation has achieved remarkable progress in instruction following and aesthetics. However, a persistent challenge is the prevalence of physical artifacts, such as anatomical and structural flaws, which severely degrade perceptual quality and limit application. Given the diversity and complexity of these artifacts, a systematic and fine-grained evaluation framework is required, which is lacking in current benchmarks. To fill this gap, we introduce MagicMirror, a comprehens…

BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis
Florian Kofler, Marcel Rosier, Mehdi Astaraki, Hendrik M\"oller, Ilhem Isra Mekki, Josef A. Buchner, Anton Schmick, Arianna Pfiffer, Eva Oswald, Lucas Zimmer, Ezequiel de la Rosa, Sarthak Pati, Julian Canisius, Arianna Piffer, Ujjwal Baid, Mahyar Valizadeh, Akis Linardos, Jan C. Peeken, Surprosanna Shit, Felix Steinbauer, Daniel Rueckert, Rolf Heckemann, Spyridon Bakas, Jan Kirschke, …

BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis
BrainLesion Suite is a versatile toolkit for building modular brain lesion image analysis pipelines in Python. Following Pythonic principles, BrainLesion Suite is designed to provide a 'brainless' development experience, minimizing cognitive effort and streamlining the creation of complex workflows for clinical and scientific practice. At its core is an adaptable preprocessing module that performs co-registration, atlas registration, and optional skull-stripping and defacing on arbitrary multi-…

Filling MIDI Velocity using U-Net Image Colorizer
Zhanhong He, David Cooper, Defeng Huang, Roberto Togneri
https://arxiv.org/abs/2508.07751 https://arxiv.o…

Filling MIDI Velocity using U-Net Image Colorizer
Modern music producers commonly use MIDI (Musical Instrument Digital Interface) to store their musical compositions. However, MIDI files created with digital software may lack the expressive characteristics of human performances, essentially leaving the velocity parameter - a control for note loudness - undefined, which defaults to a flat value. The task of filling MIDI velocity is termed MIDI velocity prediction, which uses regression models to enhance music expressiveness by adjusting only th…

Time For 9 o'clock #HashTagGames hosted by @… Let's play!
#FilmCharactersViralPost

Urban Living II 🌝
都市生活 II 🌝
📷 Nikon FE
🎞️Lucky SHD 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Yiding Cao Geld mit PayPal.Me senden
Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

FVGen: Accelerating Novel-View Synthesis with Adversarial Video Diffusion Distillation
Wenbin Teng, Gonglin Chen, Haiwei Chen, Yajie Zhao
https://arxiv.org/abs/2508.06392 https:…

FVGen: Accelerating Novel-View Synthesis with Adversarial Video Diffusion Distillation
Recent progress in 3D reconstruction has enabled realistic 3D models from dense image captures, yet challenges persist with sparse views, often leading to artifacts in unseen areas. Recent works leverage Video Diffusion Models (VDMs) to generate dense observations, filling the gaps when only sparse views are available for 3D reconstruction tasks. A significant limitation of these methods is their slow sampling speed when using VDMs. In this paper, we present FVGen, a novel framework that addres…