Search Results for author:
Found 15 papers, 2 papers with code
SimpleEgo: Predicting Probabilistic Body Pose from Egocentric Cameras
This presents a challenging scenario, as parts of the body often fall outside of the image or are occluded.
Ranked #1 on
Egocentric Pose Estimation
on UnrealEgo
3DiFACE: Diffusion-based Speech-driven 3D Facial Animation and Editing
To enable stochasticity as well as motion editing, we propose a lightweight audio-conditioned diffusion model for 3D facial motion.
HMD-NeMo: Online 3D Avatar Motion Generation From Sparse Observations
Generating both plausible and accurate full body avatar motion is the key to the quality of immersive experiences in mixed reality scenarios.
Probabilistic Human Mesh Recovery in 3D Scenes from Egocentric Views
One of the biggest challenges of this task is severe body truncation due to close social distances in egocentric scenarios, which brings large pose ambiguities for unseen body parts.
Imitator: Personalized Speech-driven 3D Facial Animation
To address this, we present Imitator, a speech-driven facial expression synthesis method, which learns identity-specific details from a short input video and produces novel facial expressions matching the identity-specific speaking style and facial idiosyncrasies of the target actor.
FLAG: Flow-based 3D Avatar Generation from Sparse Observations
To represent people in mixed reality applications for collaboration and communication, we need to generate realistic and faithful avatar poses.
Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking
Despite the recent advances in multiple object tracking (MOT), achieved by joint detection and tracking, dealing with long occlusions remains a challenge.
Deep Sequence Learning for Video Anticipation: From Discrete and Deterministic to Continuous and Stochastic
Video anticipation is the task of predicting one/multiple future representation(s) given limited, partial observation.
Uncertainty Inspired RGB-D Saliency Detection
Our framework includes two main models: 1) a generator model, which maps the input image and latent variable to stochastic saliency prediction, and 2) an inference model, which gradually updates the latent variable by sampling it from the true or approximate posterior distribution.
Ranked #1 on
RGB-D Salient Object Detection
on LFSD
RGB-D Salient Object Detection
RGB Salient Object Detection
+1
A Stochastic Conditioning Scheme for Diverse Human Motion Prediction
Human motion prediction, the task of predicting future 3D human poses given a sequence of observed ones, has been mostly treated as a deterministic problem.
ArTIST: Autoregressive Trajectory Inpainting and Scoring for Tracking
One of the core components in online multiple object tracking (MOT) frameworks is associating new detections with existing tracklets, typically done via a scoring function.
Mosaic Super-resolution via Sequential Feature Pyramid Networks
Additionally, to the best of our knowledge, our method is the first specialized method to super-resolve mosaic images, whether it be multi-spectral or Bayer.
Contextually Plausible and Diverse 3D Human Motion Prediction
We tackle the task of diverse 3D human motion prediction, that is, forecasting multiple plausible future 3D poses given a sequence of observed 3D poses.
Multi-FAN: Multi-Spectral Mosaic Super-Resolution Via Multi-Scale Feature Aggregation Network
This mosaic image is then merged with the mosaic image generated by the SR network to produce a quantitatively superior image.
Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network
This paper introduces a novel method to simultaneously super-resolve and colour-predict images acquired by snapshot mosaic sensors.
