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computer vision

3,363 papers

#machine learning Preprint Sep 2026

One Shared LoRA Weight for MRI Reconstruction across Acceleration Factors

Shared LoRA is proposed, a parameter-efficient framework that freezes the pretrained SHFormer backbone and trains a single shared set of LoRA adapters together with a lightweight gating network that achieves the best or competitive PSNR and SSIM across acceleration factors.

Zhi-Wei Zhao, Wei-Kang Gong, Zhongnian Li et al. · 0 citations
#machine learning Open access Sep 2026

Deep learning from the crowd. Fundamentals of morphological galaxy classification

A deep neural network model to perform galaxy morphological classification trained from crowd annotations is adapted, considering the training scheme, the agreement between the annotators, and the hierarchy, to derive useful results for upper levels in the hierarchy.

L. E. Sucar, C. del Burgo, Jonathan Serrano-Pérez · 0 citations
#machine learning Preprint Sep 2026

Spatial Attention Supervision for Defect Localization: Exploiting Ground-Truth Masks as Training Signal in Diffusion-Augmented Defect Detection

The results show that existing evaluation masks can act as practical training signals that measurably and reproducibly improve where defect classifiers attend, and contextualizing the supervised gains.

Sajjad Rezvani Boroujeni, Muskan Saraf, Gnana Tulasi Makineni et al. · 0 citations
#machine learning Preprint Sep 2026

SolarBench: A global solar energy nowcasting benchmark

As the share of solar power grows, nowcasting weather-driven solar variability becomes critical for reliable energy system operation. State-of-the-art approaches increasingly apply deep learning to sky camera and geostationary satellite observations, but fragmented datasets and inconsistent evaluation make it difficult...

Yuhao Nie, Stephen Campbell, Quentin Paletta et al. · 0 citations
#machine learning Review Sep 2026

GradeTrap: Authority Cues in Images Shift VLM Judgments Despite Explicit Instructions to Ignore Them

As vision-language models (VLMs) become increasingly capable and are deployed in consequential real-world settings, they must evaluate evidence independently rather than defer uncritically to human authority. We introduce GradeTrap, a controlled evaluation that places two social cues in direct conflict: a student answe...

Deep Dessai · 0 citations
#machine learning Preprint Sep 2026

Accelerating Diffusion Transformers with Gaussian Process Rectified Feature Cache

A statistical observation that the residuals between the features of full computation steps using caching methods and reference full-compute trajectory locally exhibit a zero-mean Gaussian distribution is presented, and a plug-and-play GP-Refiner correction framework is proposed.

Zhi-Rong Shen, Rui-Xin Huang, Chang Zou et al. · 0 citations
#machine learning Preprint Sep 2026

Gaussian Linear Functional Manifold Method for Massive Point Cloud Data

The Gaussian Linear Functional Manifold (GLFM), a physics-informed statistical framework that represents continuous surface topography using deterministic linear functional bases while modeling microscale diffuse laser backscatter as an isotropic Gaussian process, is introduced.

Hong Zhao, Tong-Lin Zhang, Bai-Jian Yang et al. · 0 citations
#machine learning Preprint Sep 2026

RenderFormer-V2: Neural Rendering with Heterogeneous Scene Primitives

We present'RenderFormer-V2', a unified learned transformer-based neural rendering model, complementary to modern physics-based rendering systems, that can handle diverse light-transport effects such as caustics, volumetric scattering, environment lighting, textured and displaced surfaces and out-of-distribution materia...

Chong Zeng, Yue Dong, P. Peers et al. · 0 citations
#machine learning Preprint Open access Sep 2026

Srijika: OpenType-Layout-Reusing Font Restyling for Nine Indic Scripts

We present Srijika, a system for producing installable OpenType fonts for nine Brahmic scripts: Devanagari, Tamil, Bengali, Telugu, Kannada, Malayalam, Gujarati, Gurmukhi, and Odia. Rather than generating fonts from scratch, Srijika restyles glyph outlines from shaping-complete template fonts. It preserves the template...

Anil Pai · 0 citations
#machine learning Preprint Sep 2026

SimpleMemVLA: A Simple but Effective Native-Video Memory for Vision-Language-Action Models

SimpleMemVLA, a VLA without a dedicated memory module that uses the backbone's native video context directly as memory, achieves state-of-the-art results on four memory benchmarks without loss on general-purpose control, and with the same backbone and training setup it outperforms retrieval, compression and recurrent-s...

C. Yin, Wang Xu, Jun-Peng Yang et al. · 2 citations
#machine learning Preprint Open access Sep 2026

A Specialized Large Multimodal Model for Interpreting PET/CT in Head and Neck Cancer

Background: Diagnosing head and neck cancer using PET/CT is clinically challenging and time-consuming due to the anatomical complexity of the region, motivating computer-aided diagnosis (CAD). Generalist Large Multimodal Models (LMMs) remain limited in medical contexts by insufficient domain-specific knowledge, privacy...

Haengbok Chung, SunGyu Kim, Joo hyun Lee et al. · 0 citations

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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