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Found 12 papers, 5 papers with code
SCRREAM : SCan, Register, REnder And Map:A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark
However, using these datasets to evaluate dense geometry tasks, such as depth rendering, can be problematic as the meshes of the dataset are often incomplete and may produce wrong ground truth to evaluate the details.
HouseCat6D - A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios
Estimating 6D object poses is a major challenge in 3D computer vision.
VoxNeRF: Bridging Voxel Representation and Neural Radiance Fields for Enhanced Indoor View Synthesis
The generation of high-fidelity view synthesis is essential for robotic navigation and interaction but remains challenging, particularly in indoor environments and real-time scenarios.
Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model
Text-driven human motion generation in computer vision is both significant and challenging.
Ranked #17 on
Motion Synthesis
on KIT Motion-Language
Dynamic Hyperbolic Attention Network for Fine Hand-object Reconstruction
In this work, we propose the first precise hand-object reconstruction method in hyperbolic space, namely Dynamic Hyperbolic Attention Network (DHANet), which leverages intrinsic properties of hyperbolic space to learn representative features.
Incremental 3D Semantic Scene Graph Prediction from RGB Sequences
Our method consists of a novel incremental entity estimation pipeline and a scene graph prediction network.
HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios
Estimating 6D object poses is a major challenge in 3D computer vision.
MonoGraspNet: 6-DoF Grasping with a Single RGB Image
6-DoF robotic grasping is a long-lasting but unsolved problem.
Bending Graphs: Hierarchical Shape Matching using Gated Optimal Transport
Shape matching has been a long-studied problem for the computer graphics and vision community.
SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences
Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks.
Ranked #1 on
3D Object Classification
on 3R-Scan
SCFusion: Real-time Incremental Scene Reconstruction with Semantic Completion
We propose a framework that ameliorates this issue by performing scene reconstruction and semantic scene completion jointly in an incremental and real-time manner, based on an input sequence of depth maps.
