Search Results for author:
Found 12 papers, 9 papers with code
VIBE: Video Inference for Human Body Pose and Shape Estimation
Human motion is fundamental to understanding behavior.
Ranked #33 on
Monocular 3D Human Pose Estimation
on Human3.6M
TEACH: Temporal Action Composition for 3D Humans
In particular, our goal is to enable the synthesis of a series of actions, which we refer to as temporal action composition.
BABEL: Bodies, Action and Behavior with English Labels
To address this, we present BABEL, a large dataset with language labels describing the actions being performed in mocap sequences.
Ranked #1 on
Action Classification
on BABEL
Learning to Regress Bodies from Images using Differentiable Semantic Rendering
For Minimally-Clothed regions, we define the DSR-MC loss, which encourages a tight match between a rendered SMPL body and the minimally-clothed regions of the image.
Ranked #51 on
3D Human Pose Estimation
on 3DPW
(using extra training data)
NTUA-SLP at SemEval-2018 Task 3: Tracking Ironic Tweets using Ensembles of Word and Character Level Attentive RNNs
In this paper we present two deep-learning systems that competed at SemEval-2018 Task 3 "Irony detection in English tweets".
NTUA-SLP at SemEval-2018 Task 1: Predicting Affective Content in Tweets with Deep Attentive RNNs and Transfer Learning
In this paper we present deep-learning models that submitted to the SemEval-2018 Task~1 competition: "Affect in Tweets".
NTUA-SLP at SemEval-2018 Task 2: Predicting Emojis using RNNs with Context-aware Attention
In this paper we present a deep-learning model that competed at SemEval-2018 Task 2 "Multilingual Emoji Prediction".
Emotional Speech-driven 3D Body Animation via Disentangled Latent Diffusion
Once trained, AMUSE synthesizes 3D human gestures directly from speech with control over the expressed emotions and style by combining the content from the driving speech with the emotion and style of another speech sequence.
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activations
Neural activation models have been proposed in the literature that use a set of example words for which fMRI measurements are available in order to find a mapping between word semantics and localized neural activations.
Cross-topic distributional semantic representations via unsupervised mappings
In traditional Distributional Semantic Models (DSMs) the multiple senses of a polysemous word are conflated into a single vector space representation.
SINC: Spatial Composition of 3D Human Motions for Simultaneous Action Generation
Motivated by the observation that the correspondence between actions and body parts is encoded in powerful language models, we extract this knowledge by prompting GPT-3 with text such as "what are the body parts involved in the action <action name>?
RHOBIN Challenge: Reconstruction of Human Object Interaction
Modeling the interaction between humans and objects has been an emerging research direction in recent years.
