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Found 25 papers, 13 papers with code
BundleMoCap: Efficient, Robust and Smooth Motion Capture from Sparse Multiview Videos
It solves the motion capture task in a single stage, eliminating the need for temporal smoothness objectives while still delivering smooth motions.
3D human pose and shape estimation
Markerless Motion Capture
Noise-in, Bias-out: Balanced and Real-time MoCap Solving
By relying on a unified representation, we show that training such a model is not bound to high-end MoCap training data acquisition, and exploit the advances in marker-less MoCap to acquire the necessary data.
KBody: Towards general, robust, and aligned monocular whole-body estimation
It follows a predict-and-optimize approach, relying on data-driven model estimates for the constraints that will be used to solve for the body's parameters.
Hybrid Skip: A Biologically Inspired Skip Connection for the UNet Architecture
In this work we introduce a biologically inspired long-range skip connection for the UNet architecture that relies on the perceptual illusion of hybrid images, being images that simultaneously encode two images.
Monocular Spherical Depth Estimation with Explicitly Connected Weak Layout Cues
Spherical cameras capture scenes in a holistic manner and have been used for room layout estimation.
A Low-Cost & Real-Time Motion Capture System
Traditional marker-based motion capture requires excessive and specialized equipment, hindering accessibility and wider adoption.
Towards Full-to-Empty Room Generation with Structure-Aware Feature Encoding and Soft Semantic Region-Adaptive Normalization
In order to acquire photo-realistic and structural consistent background, existing deep learning methods either employ image inpainting approaches or incorporate the learning of the scene layout as an individual task and leverage it later in a not fully differentiable semantic region-adaptive normalization module.
A benchmark with decomposed distribution shifts for 360 monocular depth estimation
In this work we contribute a distribution shift benchmark for a computer vision task; monocular depth estimation.
On Coordinate Decoding for Keypoint Estimation Tasks
A series of 2D (and 3D) keypoint estimation tasks are built upon heatmap coordinate representation, i. e. a probability map that allows for learnable and spatially aware encoding and decoding of keypoint coordinates on grids, even allowing for sub-pixel coordinate accuracy.
HUMAN4D: A Human-Centric Multimodal Dataset for Motions and Immersive Media
HUMAN4D is introduced to the computer vision and graphics research communities to enable joint research on spatio-temporally aligned pose, volumetric, mRGBD and audio data cues.
Pano3D: A Holistic Benchmark and a Solid Baseline for $360^o$ Depth Estimation
Pano3D is a new benchmark for depth estimation from spherical panoramas.
Serverless Streaming for Emerging Media: Towards 5G Network-Driven Cost Optimization
Immersive 3D media is an emerging type of media that captures, encodes and reconstructs the 3D appearance of people and objects, with applications in tele-presence, teleconference, entertainment, gaming and other fields.
Networking and Internet Architecture Multimedia
Single-Shot Cuboids: Geodesics-based End-to-end Manhattan Aligned Layout Estimation from Spherical Panoramas
In this work we show how to estimate full room layouts in a single-shot, eliminating the need for postprocessing.
[Re] On end-to-end 6{DoF} object pose estimation and robustness to object scale
We communicated with the authors of [1] through GitHub, and we would like to thank them as they provided a fast and detailed response.
SHREC 2020 track: 6D Object Pose Estimation
From captured color and depth images, we use this simulator to generate a 3D dataset which has 400 photo-realistic synthesized color-and-depth image pairs with various view angles for training, and another 100 captured and synthetic images for testing.
DronePose: Photorealistic UAV-Assistant Dataset Synthesis for 3D Pose Estimation via a Smooth Silhouette Loss
In this context, the 3D localisation of the UAV assistant is an important task that can facilitate the exchange of spatial information between the user and the UAV.
Ranked #1 on
Drone Pose Estimation
on UAVA
Deep Lighting Environment Map Estimation from Spherical Panoramas
We approach this problem differently, exploiting the availability of surface geometry to employ image-based relighting as a data generator and supervision mechanism.
Deep Soft Procrustes for Markerless Volumetric Sensor Alignment
This is accomplished by a soft, differentiable procrustes analysis that regularizes the segmentation and achieves higher extrinsic calibration performance in expanded sensor placement configurations, while being unrestricted by the number of sensors of the volumetric capture system.
Restyling Data: Application to Unsupervised Domain Adaptation
Machine learning is driven by data, yet while their availability is constantly increasing, training data require laborious, time consuming and error-prone labelling or ground truth acquisition, which in some cases is very difficult or even impossible.
Spherical View Synthesis for Self-Supervised 360 Depth Estimation
This has led to the utilization of view synthesis as an indirect objective for learning depth estimation using efficient data acquisition procedures.
$360^o$ Surface Regression with a Hyper-Sphere Loss
We present a dataset of $360^o$ images of indoor spaces with their corresponding ground truth surface normal, and train a deep convolutional neural network (CNN) on the task of monocular 360 surface estimation.
A Low-Cost, Flexible and Portable Volumetric Capturing System
Multi-view capture systems are complex systems to engineer.
Self-Supervised Deep Depth Denoising
Specifically, the proposed autoencoder exploits multiple views of the same scene from different points of view in order to learn to suppress noise in a self-supervised end-to-end manner using depth and color information during training, yet only depth during inference.
OmniDepth: Dense Depth Estimation for Indoors Spherical Panoramas
Recent work on depth estimation up to now has only focused on projective images ignoring 360 content which is now increasingly and more easily produced.
Ranked #18 on
Depth Estimation
on Stanford2D3D Panoramic
An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing
The latest developments in 3D capturing, processing, and rendering provide means to unlock novel 3D application pathways.
