755 citations · 4.3k across the 133 of their papers we have counts for
15 papers · 1 filter
An Anatomy of Vision-Language-Action Models: From Modules to Milestones and Challenges
Chao Xu, Suyu Zhang, Yang Liu +11
Vision-Language-Action (VLA) models are driving a revolution in robotics, enabling machines to understand instructions and interact with the physical world. This field is exploding…
EEG-D3: A Solution to the Hidden Overfitting Problem of Deep Learning Models
Siegfried Ludwig, Stylianos Bakas, Konstantinos Barmpas +5
Deep learning for decoding EEG signals has gained traction, with many claims to state-of-the-art accuracy. However, despite the convincing benchmark performance, successful transla…
ReasonX: MLLM-Guided Intrinsic Image Decomposition
Alara Dirik, Tuanfeng Wang, Duygu Ceylan +2
Intrinsic image decomposition aims to separate images into physical components such as albedo, depth, normals, and illumination. While recent diffusion- and transformer-based model…
STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits
Foivos Paraperas Papantoniou, Stathis Galanakis, Rolandos Alexandros Potamias +2
This paper presents STARCaster, an identity-aware spatio-temporal video diffusion model that addresses both speech-driven portrait animation and dynamic viewpoint control, given an…
ImHead: A Large-scale Implicit Morphable Model for Localized Head Modeling
Rolandos Alexandros Potamias, Stathis Galanakis, Jiankang Deng +2
Over the last years, 3D morphable models (3DMMs) have emerged as a state-of-the-art methodology for modeling and generating expressive 3D avatars. However, given their reliance on…
ID-Consistent, Precise Expression Generation with Blendshape-Guided Diffusion
Foivos Paraperas Papantoniou, Stefanos Zafeiriou
Human-centric generative models designed for AI-driven storytelling must bring together two core capabilities: identity consistency and precise control over human performance. Whil…
NeuroRVQ: Multi-Scale Biosignal Tokenization for Generative Foundation Models
Konstantinos Barmpas, Na Lee, Dimitrios Chalatsis +7
Biosignals such as electroencephalography (EEG), electrocardiography (ECG), and electromyography (EMG) encode physiological activity across multiple temporal and spectral scales, y…
Embodied Arena: A Comprehensive, Unified, and Evolving Evaluation Platform for Embodied AI
Fei Ni, Min Zhang, Pengyi Li +34
Embodied AI development significantly lags behind large foundation models due to three critical challenges: (1) lack of systematic understanding of core capabilities needed for Emb…
Geometric Neural Distance Fields for Learning Human Motion Priors
Zhengdi Yu, Simone Foti, Linguang Zhang +4
We introduce Neural Riemannian Motion Fields (NRMF), a novel 3D generative human motion prior that enables robust, temporally consistent, and physically plausible 3D motion recover…
Large Learning Rates Simultaneously Achieve Robustness to Spurious Correlations and Compressibility
Melih Barsbey, Lucas Prieto, Stefanos Zafeiriou +1
Robustness and resource-efficiency are two highly desirable properties for modern machine learning models. However, achieving them jointly remains a challenge. In this paper, we id…
Are Large Brainwave Foundation Models Capable Yet? Insights from Fine-tuning
Na Lee, Konstantinos Barmpas, Yannis Panagakis +3
Foundation Models have demonstrated significant success across various domains in Artificial Intelligence (AI), yet their capabilities for brainwave modeling remain unclear. In thi…
PRISM: A Unified Framework for Photorealistic Reconstruction and Intrinsic Scene Modeling
Alara Dirik, Tuanfeng Wang, Duygu Ceylan +2
We present PRISM, a unified framework that enables multiple image generation and editing tasks in a single foundational model. Starting from a pre-trained text-to-image diffusion m…
Advancing Brainwave Modeling with a Codebook-Based Foundation Model
Konstantinos Barmpas, Na Lee, Yannis Panagakis +3
Recent advances in large-scale pre-trained Electroencephalogram (EEG) models have shown great promise, driving progress in Brain-Computer Interfaces (BCIs) and healthcare applicati…
SpinMeRound: Consistent Multi-View Identity Generation Using Diffusion Models
Stathis Galanakis, Alexandros Lattas, Stylianos Moschoglou +2
Despite recent progress in diffusion models, generating realistic head portraits from novel viewpoints remains a significant challenge. Most current approaches are constrained to l…
Arc2Avatar: Generating Expressive 3D Avatars from a Single Image via ID Guidance
Dimitrios Gerogiannis, Foivos Paraperas Papantoniou, Rolandos Alexandros Potamias +2
Inspired by the effectiveness of 3D Gaussian Splatting (3DGS) in reconstructing detailed 3D scenes within multi-view setups and the emergence of large 2D human foundation models, w…