Search Results for author:
Found 29 papers, 11 papers with code
Align3R: Aligned Monocular Depth Estimation for Dynamic Videos
Recent developments in monocular depth estimation methods enable high-quality depth estimation of single-view images but fail to estimate consistent video depth across different frames.
GausSurf: Geometry-Guided 3D Gaussian Splatting for Surface Reconstruction
3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities.
NASM: Neural Anisotropic Surface Meshing
To our knowledge, this is the first time that a deep learning framework and a large dataset are proposed to construct a high-d Euclidean embedding space for 3D anisotropic surface meshing.
NoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models
This approach allows the model to more precisely adapt to specific tasks while maintaining a compact parameter space.
Domain-invariant Representation Learning via Segment Anything Model for Blood Cell Classification
To address this issue, we propose a novel framework of domain-invariant representation learning (DoRL) via segment anything model (SAM) for blood cell classification.
DICE: End-to-end Deformation Capture of Hand-Face Interactions from a Single Image
The first and only method for hand-face interaction recovery, Decaf, introduces a global fitting optimization guided by contact and deformation estimation networks trained on studio-collected data with 3D annotations.
DreamMat: High-quality PBR Material Generation with Geometry- and Light-aware Diffusion Models
2D diffusion model, which often contains unwanted baked-in shading effects and results in unrealistic rendering effects in the downstream applications.
Part123: Part-aware 3D Reconstruction from a Single-view Image
However, all the existing methods represent the target object as a closed mesh devoid of any structural information, thus neglecting the part-based structure, which is crucial for many downstream applications, of the reconstructed shape.
Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention
Specifically, these methods assume that the input images should comply with a predefined camera type, e. g. a perspective camera with a fixed focal length, leading to distorted shapes when the assumption fails.
Adaptive Surface Normal Constraint for Geometric Estimation from Monocular Images
We introduce a novel approach to learn geometries such as depth and surface normal from images while incorporating geometric context.
Coverage Axis++: Efficient Inner Point Selection for 3D Shape Skeletonization
We introduce Coverage Axis++, a novel and efficient approach to 3D shape skeletonization.
Disentangled Clothed Avatar Generation from Text Descriptions
In this paper, we introduce a novel text-to-avatar generation method that separately generates the human body and the clothes and allows high-quality animation on the generated avatar.
Surf-D: Generating High-Quality Surfaces of Arbitrary Topologies Using Diffusion Models
The experiments demonstrate the superior performance of Surf-D in shape generation across multiple modalities as conditions.
Wonder3D: Single Image to 3D using Cross-Domain Diffusion
In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images. Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover 3D geometry from 2D diffusion priors, but they typically suffer from time-consuming per-shape optimization and inconsistent geometry.
Ranked #2 on
Single-View 3D Reconstruction
on GSO
SyncDreamer: Generating Multiview-consistent Images from a Single-view Image
In this paper, we present a novel diffusion model called that generates multiview-consistent images from a single-view image.
Ranked #3 on
Single-View 3D Reconstruction
on GSO
NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects from Multiview Images
We present a neural rendering-based method called NeRO for reconstructing the geometry and the BRDF of reflective objects from multiview images captured in an unknown environment.
NeuralUDF: Learning Unsigned Distance Fields for Multi-view Reconstruction of Surfaces with Arbitrary Topologies
In this paper, we propose to represent surfaces as the Unsigned Distance Function (UDF) and develop a new volume rendering scheme to learn the neural UDF representation.
TORE: Token Reduction for Efficient Human Mesh Recovery with Transformer
We further demonstrate the generalizability of our method on hand mesh recovery.
SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Views
We introduce SparseNeuS, a novel neural rendering based method for the task of surface reconstruction from multi-view images.
To What Extent Do Disadvantaged Neighborhoods Mediate Social Assistance Dependency? Evidence from Sweden
In this paper, we build on the theory of cumulative disadvantage and examine whether the accumulated use of social assistance over the life course is associated with an increased risk of future social assistance recipiency.
3PSDF: Three-Pole Signed Distance Function for Learning Surfaces with Arbitrary Topologies
The key to our method is the introduction of a new sign, the NULL sign, in addition to the conventional in and out labels.
Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images
In this paper, we present a generalizable model-free 6-DoF object pose estimator called Gen6D.
Adaptive Surface Normal Constraint for Depth Estimation
We present a novel method for single image depth estimation using surface normal constraints.
Point2Skeleton: Learning Skeletal Representations from Point Clouds
We introduce Point2Skeleton, an unsupervised method to learn skeletal representations from point clouds.
Learnable Motion Coherence for Correspondence Pruning
We propose a novel formulation of fitting coherent motions with a smooth function on a graph of correspondences and show that this formulation allows a closed-form solution by graph Laplacian.
Adaptive Compact Attention For Few-shot Video-to-video Translation
This paper proposes an adaptive compact attention model for few-shot video-to-video translation.
SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform
Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications.
Modeling 3D Shapes by Reinforcement Learning
We explore how to enable machines to model 3D shapes like human modelers using deep reinforcement learning (RL).
Floorplan-Jigsaw: Jointly Estimating Scene Layout and Aligning Partial Scans
We present a novel approach to align partial 3D reconstructions which may not have substantial overlap.
