/Paperlist

Important papers for my research topics: point cloud analysis, unsupervised learning, etc.

Basics

MRF tutorial

VAE tutorial

Spectral Clustering tutorial


Point Cloud Understanding

Basic architecture

ICLR22 PointMLP Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

CVPR17 PointSetGeneration A Point Set Generation Network for 3D Object Reconstruction from a Single Image

Instance segmentation

CVPR19 GSPN GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud

Scene flow

NIPS21 Neural Scene Flow Prior

CVPR21 Flowstep3D FlowStep3D: Model Unrolling for Self-Supervised Scene Flow Estimation


Image Understanding

Instance segmentation

21 Mask2Former Masked-attention Mask Transformer for Universal Image Segmentation

NIPS21 MaskFormer Per-Pixel Classification is Not All You Need for Semantic Segmentation

NIPS21 K-Net K-Net: Towards Unified Image Segmentation


Motion Segmentation

2D motion segmentation

CVPR21 DyStaB DyStaB: Unsupervised Object Segmentation via Dynamic-Static Bootstrapping

Layered models

CVPR17 MR-Flow Optical Flow in Mostly Rigid Scenes

CVPR16 SOF Optical Flow With Semantic Segmentation and Localized Layers

CVPR13 FC-2Layers A Fully-Connected Layered Model of Foreground and Background Flow

CVPR12 nLayers Layered segmentation and optical flow estimation over time

NIPS10 Layers++ Layered Image Motion with Explicit Occlusions, Temporal Consistency, and Depth Ordering

Robotics-related

22 Automatic Labeling to Generate Training Data for Online LiDAR-based Moving Object Segmentation

RAL21 LMNet Moving object segmentation in 3D LiDAR data: A learning-based approach exploiting sequential data

IROS19 SelfDeepMask Self-supervised Transfer Learning for Instance Segmentation through Physical Interaction


Representation Learning

Learning by compression

21 Equivalences Between Sparse Models and Neural Networks

NIPS20 MCR2 Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction

00 Information bottleneck The information bottleneck method

Contrastive learning

3DV21 PoseContrast PoseContrast: Class-Agnostic Object Viewpoint Estimation in the Wild with Pose-Aware Contrastive Learning

ICCV21 DepthContrast Self-Supervised Pretraining of 3D Features on Any Point-Cloud

CVPR21 ContrastiveSceneContexts Exploring Data-Efficient 3D Scene Understanding With Contrastive Scene Contexts

NIPS20 InfoMin What Makes for Good Views for Contrastive Learning?

ECCV20 PointContrast PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding

Object-centric learning / Unsupervised segmentation

21 PPD Unsupervised Pose-Aware Part Decomposition for 3D Articulated Objects

NIPS21 SIMONe SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition

ICCV21 InSeGAN InSeGAN: A Generative Approach to Segmenting Identical Instances in Depth Images

NIPS20 MulMON Learning Object-Centric Representations of Multi-Object Scenes from Multiple View

ICLR20 Genesis GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations

ICCV19 BAE-Net BAE-NET: Branched Autoencoder for Shape Co-Segmentation