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Home/Authors/Piotr Koniusz

Piotr Koniusz

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 14, 2026, 11:22 PM AMS

29

papers

607

total citations

papers (29)

On Learning the Geodesic Path for Incremental Learning

Rethinking Class Relations: Absolute-Relative Supervised and Unsupervised Few-Shot Learning

3Mformer: Multi-Order Multi-Mode Transformer for Skeletal Action Recognition

Transductive Few-Shot Learning With Prototype-Based Label Propagation by Iterative Graph Refinement

Uncertainty-DTW for Time Series and Sequences

Few-Shot Keypoint Detection With Uncertainty Learning for Unseen Species

Distilling Self-Supervised Vision Transformers for Weakly-Supervised Few-Shot Classification & Segmentation

Time-rEversed diffusioN tEnsor Transformer: A New TENET of Few-Shot Object Detection

Manifold Learning Benefits GANs

Learnable Expansion of Graph Operators for Multi-Modal Feature Fusion

Robust Distillation via Untargeted and Targeted Intermediate Adversarial Samples

Pre-training with Random Orthogonal Projection Image Modeling

Learning Partial Correlation Based Deep Visual Representation for Image Classification

Detect Any Keypoints: An Efficient Light-Weight Few-Shot Keypoint Detector

Adversarially Robust Few-shot Learning via Parameter Co-distillation of Similarity and Class Concept Learners

CHAIN: Enhancing Generalization in Data-Efficient GANs via lipsCHitz continuity constrAIned Normalization

Open-World Objectness Modeling Unifies Novel Object Detection

BiLoRA: Almost-Orthogonal Parameter Spaces for Continual Learning

Few-shot Action Recognition with Permutation-invariant Attention

Graph Your Own Prompt

NEURIPS 2025arXiv

On Modulating the Gradient for Meta-Learning

EASE: Unsupervised Discriminant Subspace Learning for Transductive Few-Shot Learning

Kernelized Few-Shot Object Detection With Efficient Integral Aggregation

Generalized Laplacian Eigenmaps

Learning Spatial-context-aware Global Visual Feature Representation for Instance Image Retrieval

Robustifying Zero-Shot Vision Language Models by Subspaces Alignment

Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective

NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs

Adaptive Subspaces for Few-Shot Learning