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Found 8 papers, 3 papers with code
3D Visibility-aware Generalizable Neural Radiance Fields for Interacting Hands
Subsequently, a feature fusion module that exploits the visibility of query points and mesh vertices is introduced to adaptively merge features of both hands, enabling the recovery of features in unseen areas.
Monocular 3D Hand Mesh Recovery via Dual Noise Estimation
However, due to the fixed hand topology and complex hand poses, current models are hard to generate meshes that are aligned with the image well.
Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning
Existing methods are restricted in this setting as they estimate garment warping flows mainly based on 2D poses and appearance, which omits the geometric prior of the 3D human body shape.
BodyGAN: General-Purpose Controllable Neural Human Body Generation
This is because current methods mainly rely on a single pose/appearance model, which is limited in disentangling various poses and appearance in human images.
Instance-Aware Representation Learning and Association for Online Multi-Person Tracking
Multi-Person Tracking (MPT) is often addressed within the detection-to-association paradigm.
Multi-column Point-CNN for Sketch Segmentation
Traditional sketch segmentation methods mainly rely on handcrafted features and complicate models, and their performance is far from satisfactory due to the abstract representation of sketches.
Beyond Context: Exploring Semantic Similarity for Tiny Face Detection
Tiny face detection aims to find faces with high degrees of variability in scale, resolution and occlusion in cluttered scenes.
Structured Inhomogeneous Density Map Learning for Crowd Counting
In this paper, we aim at tackling the problem of crowd counting in extremely high-density scenes, which contain hundreds, or even thousands of people.
