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Found 13 papers, 5 papers with code
X-MIC: Cross-Modal Instance Conditioning for Egocentric Action Generalization
Lately, there has been growing interest in adapting vision-language models (VLMs) to image and third-person video classification due to their success in zero-shot recognition.
DiffH2O: Diffusion-Based Synthesis of Hand-Object Interactions from Textual Descriptions
In the grasping stage, the model only generates hand motions, whereas in the interaction phase both hand and object poses are synthesized.
DIG: Draping Implicit Garment over the Human Body
Existing data-driven methods for draping garments over human bodies, despite being effective, cannot handle garments of arbitrary topology and are typically not end-to-end differentiable.
Drivable Volumetric Avatars using Texel-Aligned Features
To circumvent this, we propose a novel volumetric avatar representation by extending mixtures of volumetric primitives to articulated objects.
DeepMesh: Differentiable Iso-Surface Extraction
Our key insight is that by reasoning on how implicit field perturbations impact local surface geometry, one can ultimately differentiate the 3D location of surface samples with respect to the underlying deep implicit field.
Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches
Reconstructing 3D shape from 2D sketches has long been an open problem because the sketches only provide very sparse and ambiguous information.
Unsupervised Domain Adaptation with Temporal-Consistent Self-Training for 3D Hand-Object Joint Reconstruction
Deep learning-solutions for hand-object 3D pose and shape estimation are now very effective when an annotated dataset is available to train them to handle the scenarios and lighting conditions they will encounter at test time.
Generative Adversarial Network
Unsupervised Domain Adaptation
MeshSDF: Differentiable Iso-Surface Extraction
Unfortunately, these methods are often not suitable for applications that require an explicit mesh-based surface representation because converting an implicit field to such a representation relies on the Marching Cubes algorithm, which cannot be differentiated with respect to the underlying implicit field.
UCLID-Net: Single View Reconstruction in Object Space
Most state-of-the-art deep geometric learning single-view reconstruction approaches rely on encoder-decoder architectures that output either shape parametrizations or implicit representations.
Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation
We present a lightweight solution to recover 3D pose from multi-view images captured with spatially calibrated cameras.
Ranked #4 on
3D Human Pose Estimation
on Total Capture
Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data
CNN-based volumetric methods that label individual voxels now dominate the field of biomedical segmentation.
NeuralSampler: Euclidean Point Cloud Auto-Encoder and Sampler
Most algorithms that rely on deep learning-based approaches to generate 3D point sets can only produce clouds containing fixed number of points.
Low-Dimensionality Calibration Through Local Anisotropic Scaling for Robust Hand Model Personalization
We present a robust algorithm for personalizing a sphere-mesh tracking model to a user from a collection of depth measurements.
