State of the Art in Dense Monocular Non‐Rigid 3D Reconstruction
Abstract 3D reconstruction of deformable (or non‐rigid) scenes from a set of monocular 2D
image observations is a long‐standing and actively researched area of computer vision and …
image observations is a long‐standing and actively researched area of computer vision and …
Tracking everything everywhere all at once
We present a new test-time optimization method for estimating dense and long-range motion
from a video sequence. Prior optical flow or particle video tracking algorithms typically …
from a video sequence. Prior optical flow or particle video tracking algorithms typically …
Banmo: Building animatable 3d neural models from many casual videos
Prior work for articulated 3D shape reconstruction often relies on specialized multi-view and
depth sensors or pre-built deformable 3D models. Such methods do not scale to diverse sets …
depth sensors or pre-built deformable 3D models. Such methods do not scale to diverse sets …
Magicpony: Learning articulated 3d animals in the wild
We consider the problem of predicting the 3D shape, articulation, viewpoint, texture, and
lighting of an articulated animal like a horse given a single test image as input. We present a …
lighting of an articulated animal like a horse given a single test image as input. We present a …
Particle video revisited: Tracking through occlusions using point trajectories
Tracking pixels in videos is typically studied as an optical flow estimation problem, where
every pixel is described with a displacement vector that locates it in the next frame. Even …
every pixel is described with a displacement vector that locates it in the next frame. Even …
Neural surface reconstruction of dynamic scenes with monocular rgb-d camera
Abstract We propose Neural-DynamicReconstruction (NDR), a template-free method to
recover high-fidelity geometry and motions of a dynamic scene from a monocular RGB-D …
recover high-fidelity geometry and motions of a dynamic scene from a monocular RGB-D …
Unsupervised learning of efficient geometry-aware neural articulated representations
We propose an unsupervised method for 3D geometry-aware representation learning of
articulated objects, in which no image-pose pairs or foreground masks are used for training …
articulated objects, in which no image-pose pairs or foreground masks are used for training …
Reconstructing animatable categories from videos
Building animatable 3D models is challenging due to the need for 3D scans, laborious
registration, and manual rigging. Recently, differentiable rendering provides a pathway to …
registration, and manual rigging. Recently, differentiable rendering provides a pathway to …
Visibility aware human-object interaction tracking from single rgb camera
Capturing the interactions between humans and their environment in 3D is important for
many applications in robotics, graphics, and vision. Recent works to reconstruct the 3D …
many applications in robotics, graphics, and vision. Recent works to reconstruct the 3D …
Ppr: Physically plausible reconstruction from monocular videos
Given monocular videos, we build 3D models of articulated objects and environments
whose 3D configurations satisfy dynamics and contact constraints. At its core, our method …
whose 3D configurations satisfy dynamics and contact constraints. At its core, our method …