https://github.com/mlvlab/spotr
공식 코드Self-positioning Point-based Transformer for Point Cloud Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Encoding and reconstruction of 3D point clouds.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Self-positioning Point-based Transformer for Point Cloud Understanding
diffConv: Analyzing Irregular Point Clouds with an Irregular View
CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding
Beyond First Impressions: Integrating Joint Multi-modal Cues for Comprehensive 3D Representation
PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape Representation
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark
PointLLM: Empowering Large Language Models to Understand Point Clouds
TetraSphere: A Neural Descriptor for O(3)-Invariant Point Cloud Analysis
Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds
Classifying Objects in 3D Point Clouds Using Recurrent Neural Network: A GRU LSTM Hybrid Approach
ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding
Local and Global Point Cloud Reconstruction for 3D Hand Pose Estimation
Risk-optimized Outlier Removal for Robust 3D Point Cloud Classification
Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning
Point Cloud Mamba: Point Cloud Learning via State Space Model
MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning
Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis
Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point Clouds
CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-training
Sculpting Holistic 3D Representation in Contrastive Language-Image-3D Pre-training
3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction From a Single Image
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.