There are 4 repositories under neurips-2021 topic.
[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
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Official implementation of the NeurIPS 2021 paper "Panoptic 3D Scene Reconstruction from a Single RGB Image"
Dense Unsupervised Learning for Video Segmentation (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)
Official implementation of CATs
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Neural Scene Flow Prior (NeurIPS 2021 spotlight)
[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects
[NeurIPS 2021] Official implementation of the paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
[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.
Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch (NeurIPS 2021)
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 networks and public datasets.
Code for "Learning Graph Cellular Automata" (NeurIPS 2021).
Unsupervised Part Discovery from Contrastive Reconstruction (NeurIPS 2021)
Progressive Coordinate Transforms for Monocular 3D Object Detection, NeurIPS 2021
[NeurIPS 2021] ORL: Unsupervised Object-Level Representation Learning from Scene Images
Codes for NeurIPS 2021 paper "Adversarial Neuron Pruning Purifies Backdoored Deep Models"
Learning Graph Models for Retrosynthesis Prediction (NeurIPS 2021)
Code of the NeurIPS 2021 paper: Language and Visual Entity Relationship Graph for Agent Navigation
[NeurIPS 2021] Unsupervised Foreground Extraction via Deep Region Competition
Local explanations with uncertainty 💐!
Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective".
Robust Contrastive Learning Using Negative Samples with Diminished Semantics (NeurIPS 2021)
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
PyTorch implementation of the descriptor DEAL presented at NeurIPS 2021 "Extracting Deformation-Aware Local Features by Learning to Deform".
Out-of-distribution detection using the pNML regret. NeurIPS2021
This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.
Hyperbolic Busemann Learning with Ideal Prototypes, NeurIPS2021
(NeurIPS 2021) Realistic Evaluation of Transductive Few-Shot Learning