Georgios Tzimiropoulos

31

Papers

26

Total Citations

Papers (31)

VladVA: Discriminative Fine-tuning of LVLMs

Multiscale Vision Transformers Meet Bipartite Matching for Efficient Single-stage Action Localization

FAM Diffusion: Frequency and Attention Modulation for High-Resolution Image Generation with Stable Diffusion

Efficient Unsupervised Visual Representation Learning with Explicit Cluster Balancing

Super-FAN: Integrated Facial Landmark Localization and Super-Resolution of Real-World Low Resolution Faces in Arbitrary Poses With GANs

T-Net: Parametrizing Fully Convolutional Nets With a Single High-Order Tensor

AnimalWeb: A Large-Scale Hierarchical Dataset of Annotated Animal Faces

Affective Processes: Stochastic Modelling of Temporal Context for Emotion and Facial Expression Recognition

DivClust: Controlling Diversity in Deep Clustering

LASP: Text-to-Text Optimization for Language-Aware Soft Prompting of Vision & Language Models

How Far Are We From Solving the 2D & 3D Face Alignment Problem? (And a Dataset of 230,000 3D Facial Landmarks)

Large Pose 3D Face Reconstruction From a Single Image via Direct Volumetric CNN Regression

Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment With Limited Resources

Synergy Between Face Alignment and Tracking via Discriminative Global Consensus Optimization

Bit-Mixer: Mixed-Precision Networks With Runtime Bit-Width Selection

WarpedGANSpace: Finding Non-Linear RBF Paths in GAN Latent Space

HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces

ReGen: A good Generative Zero-Shot Video Classifier Should be Rewarded

Black Box Few-Shot Adaptation for Vision-Language Models

Bayesian Prompt Learning for Image-Language Model Generalization

FS-DETR: Few-Shot DEtection TRansformer with Prompting and without Re-Training

BATS: Binary ArchitecTure Search

EdgeViTs: Competing Light-Weight CNNs on Mobile Devices with Vision Transformers

Pre-training Strategies and Datasets for Facial Representation Learning

Edge-SD-SR: Low Latency and Parameter Efficient On-device Super-Resolution with Stable Diffusion via Bidirectional Conditioning

LAFS: Landmark-based Facial Self-supervised Learning for Face Recognition

FFF: Fixing Flawed Foundations in Contrastive Pre-Training Results in Very Strong Vision-Language Models

Project-Out Cascaded Regression With an Application to Face Alignment

Object landmark discovery through unsupervised adaptation

Unsupervised Learning of Object Landmarks via Self-Training Correspondence

Space-time Mixing Attention for Video Transformer