#计算机科学#[NeurIPS 2021] Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation, NeurIPS 2021 Spotlight
翻译 - 用于多对象跟踪和分割的原型交叉注意力网络,NeurIPS 2021 聚焦
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
#计算机科学#Official implementation of the NeurIPS 2021 paper "Panoptic 3D Scene Reconstruction from a Single RGB Image"
Dense Unsupervised Learning for Video Segmentation (NeurIPS*2021)
翻译 - 用于视频分割的密集无监督学习 (NeurIPS*2021)
[NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning
Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)
#计算机科学#Official implementation of CATs
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
#计算机科学#Neural Scene Flow Prior (NeurIPS 2021 spotlight)
[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects
#计算机科学#[NeurIPS 2021] Official implementation of the paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
#计算机科学#[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets
This repository contains the official implementation of the NeurIPS'21 paper, ROADMAP: Robust and Decomposable Average Precision for Image Retrieval.
#计算机科学#Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch (NeurIPS 2021)
#计算机科学#Fast Image Retrieval (FIRe) is an open source project to promote image retrieval research. It implements most of the major binary hashing methods to date, together with different popular backbone netw...
#计算机科学#Code for "Learning Graph Cellular Automata" (NeurIPS 2021).
Progressive Coordinate Transforms for Monocular 3D Object Detection, NeurIPS 2021
Unsupervised Part Discovery from Contrastive Reconstruction (NeurIPS 2021)
[NeurIPS 2021] ORL: Unsupervised Object-Level Representation Learning from Scene Images