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computer vision

4,009 papers

#artificial intelligence Preprint Sep 2026

ResLRP: The Role of Residual Cancellation in Attribution Instability in Vision Transformers

Residual-aware Layer-wise Relevance Propagation (ResLRP) is introduced, a simple extension of LRP whose propagation rules explicitly account for cancellations in residual branches, are exactly conservative, and provably bound relevance explosion.

Jim Berend, Reduan Achtibat, Daniel Schäffer et al. · 0 citations
#machine learning Preprint Sep 2026

From Foundation Embeddings to Cropland Maps: Label Efficiency, Temporal Transferability and Independent Human Validation

The results support frozen geospatial embeddings as a low-compute candidate for regional cropland mapping, subject to the limits of a single-state study, a 30 m-derived training reference, and a one-block human validation.

Mohammad Ammar Mughees, Giovanni Montefoschi, Zhong-Xin Chen et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

Neuro-Symbolic Hierarchical Intention Anticipation in Human Behavior

Assistive autonomous systems must anticipate human goals before an observed behavior is complete. This article formulates anticipation as goal inference from a partially observed multimodal episode together with structured prediction of the remaining behavior, rather than exact motor forecasting. A compact Hierarchical...

Farnaz Soleimani (LISSI), Abdelghani Chibani (LISSI), Yacine Amirat (LISSI) et al. · 0 citations
#machine learning Preprint Open access Sep 2026

MedPCFM-TED: One-Step Point Cloud Flow Matching for Implant Generation via Teacher-Guided Endpoint Distillation

Cranial implant generation is an important task in medical imaging. Recent point cloud based generative methods, particularly flow matching, offer strong reconstruction quality and efficient sampling, but still require multiple neural function evaluations during inference. This limits rapid generation of multiple plaus...

Kamil Kwarciak, Marek Wodzinski · 0 citations
#machine learning Preprint Sep 2026

NeuroTS-Net: Multi-Class Semantic Segmentation of Pediatric Brain Tumors in Multi-Modal MRI

NeuroTS-Net is introduced, a three-dimensional encoder-decoder convolutional neural network architecture for multi-class semantic segmentation that incorporates a dual-scale raw-detail stream, adaptive low-resolution context selection, and detail-preserving multipath downsampling that efficiently modeling broader tumor...

Darius Peteleaza, Razvan-Gabriel Dumitru, Bogdan Neamtu et al. · 0 citations
#machine learning Preprint Sep 2026

TEMPO: Learning Temporal Context for Dynamic Robot Manipulation

TEMPO is proposed, which augments a pretrained VLA with two temporal inputs: a motion summary extracted from a frozen video foundation model to resolve motion ambiguity and a compact proprioceptive history to resolve state aliasing.

Zhen-Yang Feng, Jimin Heo, Erik B. Sudderth et al. · 2 citations · ⚡1
#machine learning Preprint Sep 2026

Measuring Annotation Efficiency for Handwritten Devanagari Recognition: Sample-Complexity Curves for Four Pretraining Regimes

The scarcity in this study is constructed by subsampling a large corpus by changing only the number of real transcribed words used for fine-tuning across nine budgets from 10 to 4,000 and four initialisation regimes, with six seeds at every point.

Manglesh Kumar Pandey, S. Banshal · 0 citations
#artificial intelligence Preprint Sep 2026

Visual Cue Guided Video Planning for Generalizable Robot Navigation

CueNav is presented, a video model-based navigation framework combining visual cue guided video planning with an embodiment-specific Inverse-Dynamics Model (IDM) that paves the way toward a generalizable navigation framework for longer-horizon planning and embodiment-aware control.

Ho-Jin Lee, S. Li, Maximilian Hilger et al. · 0 citations
#machine learning Preprint Sep 2026

Can Knowledge Transfer Parameters Be Learned? LePoKet for Efficient Robotic Vision

The proposed LePoKet (Learnable Parameter Optimization for Knowledge Transfer), a structural transfer framework that embeds knowledge inheritance directly into the forward computation, demonstrates that learnable structural transfer generalizes across recognition and motion perception tasks and provides a promising app...

Y. C. Tchenko, Felix Mohr, H. Hadj-Abdelkader et al. · 0 citations
#machine learning Preprint Open access Sep 2026

Decentralized Gossip Learning and Federated Averaging for Histopathology Image Classification

Breast histopathology analysis increasingly relies on distributed learning because direct data pooling across institutions is often restricted by privacy, governance, and communication constraints. This study compares server-based Federated Averaging (FedAvg), fully decentralized gossip learning, and Hybrid Gossip-FedA...

Yusuf Ozturk, Enes Goltekin, Bengisu Atli et al. · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

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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