← Authors

Mehrtash Harandi

75 papers · 2013–2026 · 9 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) πŸ—ΊοΈ Taxonomy Completionist (129) 🌈 Renaissance Researcher (9) 🐝 Cross-Pollinator (8) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏠 Conference Loyalist (24) 🀝 Dynamic Duo (13) πŸ† Grand Slam πŸ”¬ Deep Specialist (15) πŸ† Keyword Champion (3) πŸ”₯ Unstoppable (14) πŸš€ Conference Pioneer ⚑ Prolific Year (10) πŸ—ƒοΈ Keyword Collector (278) ❓ The Questioner πŸ’Ž Century Club (73) πŸ“ˆ Trend Setter

Conferences

CVPR (24) ICCV (13) AAAI (10) WACV (9) NIPS (7) ECCV (6) ICML (4) ICLR (1) JMLR (1)

Top co-authors

Lars Petersson (13) Mathieu Salzmann (10) Pengfei Fang (9) Christian Simon (8) Yunde Jia (8) Zhi Gao (8) Yuwei Wu (8) Trung Le (7) Ali Cheraghian (6) Tom Drummond (6)

Research topics

Differential Privacy (1) Privacy (1)

Keywords

few-shot learning (12) metric learning (8) knowledge distillation (7) kernel methods (7) domain adaptation (6) manifold learning (5) representation learning (5) riemannian optimization (5) riemannian manifold (5) model compression (4) neural network (4) sparse coding (4) catastrophic forgetting (4) continual learning (4) hyperbolic space (4) dictionary learning (3) attention mechanism (3) image classification (3) semi-supervised learning (3) feature extraction (3)

Papers

Subspace-Guided Knowledge Distillation for Efficient Model Transfer WACV 2026
DIET: Machine Unlearning on a Data-Diet AAAI 2026
PCGS: Progressive Compression of 3D Gaussian Splatting AAAI 2026
Fast Feedforward 3D Gaussian Splatting Compression ICLR 2025
SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolution WACV 2025
Erasing Undesirable Influence in Diffusion Models CVPR 2025
MUNBa: Machine Unlearning via Nash Bargaining ICCV 2025
A Good Teacher Adapts Their Knowledge for Distillation ICCV 2025
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning CVPR 2024
Backpropagation-free Network for 3D Test-time Adaptation CVPR 2024
NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation CVPR 2024
Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization NIPS 2024
FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models NIPS 2024
LaViP: Language-Grounded Visual Prompting AAAI 2024
Concealing Sensitive Samples against Gradient Leakage in Federated Learning AAAI 2024
Continual Test-Time Domain Adaptation via Dynamic Sample Selection WACV 2024
Scissorhands: Scrub Data Influence via Connection Sensitivity in Networks ECCV 2024
Canonical Shape Projection is All You Need for 3D Few-shot Class Incremental Learning ECCV 2024
HAC: Hash-grid Assisted Context for 3D Gaussian Splatting Compression ECCV 2024
How Far Can We Compress Instant-NGP-Based NeRF? CVPR 2024
Hyperbolic Audio-visual Zero-shot Learning ICCV 2023
Exploring Data Geometry for Continual Learning CVPR 2023
LAVA: Label-Efficient Visual Learning and Adaptation WACV 2023
Energy-based Self-Training and Normalization for Unsupervised Domain Adaptation ICCV 2023
Vector Quantized Wasserstein Auto-Encoder ICML 2023
On Generalizing Beyond Domains in Cross-Domain Continual Learning CVPR 2022
On Enforcing Better Conditioned Meta-Learning for Rapid Few-Shot Adaptation NIPS 2022
Efficient Riemannian Meta-Optimization by Implicit Differentiation AAAI 2022
Hyperbolic Feature Augmentation via Distribution Estimation and Infinite Sampling on Manifolds NIPS 2022
Meta-Learning for Multi-Label Few-Shot Classification WACV 2022
Towards a Robust Differentiable Architecture Search Under Label Noise WACV 2022
Adaptive PoincarΓ© Point to Set Distance for Few-Shot Classification AAAI 2022
Rethinking Generalization in Few-Shot Classification NIPS 2022
Learning Instance and Task-Aware Dynamic Kernels for Few-Shot Learning ECCV 2022
Implicit Motion Handling for Video Camouflaged Object Detection CVPR 2022
Reinforced Attention for Few-Shot Learning and Beyond CVPR 2021
Semi-Supervised Metric Learning: A Deep Resurrection AAAI 2021
Learning a Gradient-free Riemannian Optimizer on Tangent Spaces AAAI 2021
Semantic-Aware Knowledge Distillation for Few-Shot Class-Incremental Learning CVPR 2021
On Learning the Geodesic Path for Incremental Learning CVPR 2021
Curvature Generation in Curved Spaces for Few-Shot Learning ICCV 2021
Kernel Methods in Hyperbolic Spaces ICCV 2021
Synthesized Feature Based Few-Shot Class-Incremental Learning on a Mixture of Subspaces ICCV 2021
Set Augmented Triplet Loss for Video Person Re-Identification WACV 2021
Adaptive Subspaces for Few-Shot Learning CVPR 2020
Revisiting Bilinear Pooling: A Coding Perspective AAAI 2020
Unsupervised Metric Learning with Synthetic Examples AAAI 2020
Devon: Deformable Volume Network for Learning Optical Flow WACV 2020
Learning from Noisy Labels via Discrepant Collaborative Training WACV 2020
Hierarchical Neural Architecture Search for Deep Stereo Matching NIPS 2020
On Modulating the Gradient for Meta-Learning ECCV 2020
Learning to Optimize on SPD Manifolds CVPR 2020
Min-Max Statistical Alignment for Transfer Learning CVPR 2019
Neural Collaborative Subspace Clustering ICML 2019
Siamese Networks: The Tale of Two Manifolds ICCV 2019
Bilinear Attention Networks for Person Retrieval ICCV 2019
Museum Exhibit Identification Challenge for the Supervised Domain Adaptation and Beyond ECCV 2018
Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective CVPR 2018
Geometry Aware Constrained Optimization Techniques for Deep Learning CVPR 2018
Learning Discriminative ab-Divergences for Positive Definite Matrices ICCV 2017
Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding NIPS 2017
Generalized Rank Pooling for Activity Recognition CVPR 2017
Joint Dimensionality Reduction and Metric Learning: A Geometric Take ICML 2017
Learning an Invariant Hilbert Space for Domain Adaptation CVPR 2017
Sparse Coding and Dictionary Learning With Linear Dynamical Systems CVPR 2016
When VLAD Met Hilbert CVPR 2016
Distribution-Matching Embedding for Visual Domain Adaptation JMLR 2016
Riemannian Coding and Dictionary Learning: Kernels to the Rescue CVPR 2015
Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs ICCV 2015
Bregman Divergences for Infinite Dimensional Covariance Matrices CVPR 2014
Optimizing Over Radial Kernels on Compact Manifolds CVPR 2014
Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution ICCV 2013
Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices CVPR 2013
Non-Linear Stationary Subspace Analysis with Application to Video Classification ICML 2013
A Framework for Shape Analysis via Hilbert Space Embedding ICCV 2013