A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

📝Conformal prediction is a user-friendly paradigm for creating statistically rigorous uncertainty sets/intervals for the predictions of such models.
https://github.com/aangelopoulos/conformal-prediction

Transformers are Sample Efficient World Models

📝Deep reinforcement learning agents are notoriously sample inefficient, which considerably limits their application to real-world problems.
https://github.com/eloialonso/iris

Text-Free Learning of a Natural Language Interface for Pretrained Face Generators

📝We propose Fast text2StyleGAN, a natural language interface that adapts pre-trained GANs for text-guided human face synthesis.
https://github.com/duxiaodan/fast_text2stylegan

Behavior Trees in Robotics and AI: An Introduction

📝A Behavior Tree (BT) is a way to structure the switching between different tasks in an autonomous agent, such as a robot or a virtual entity in a computer game.
https://github.com/BehaviorTree/BehaviorTree.CPP

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

📝The emerging paradigm of federated learning (FL) strives to enable collaborative training of deep models on the network edge without centrally aggregating raw data and hence improving data privacy.
https://github.com/adap/flower

ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech

📝Through the preliminary study on diffusion model parameterization, we find that previous gradient-based TTS models require hundreds or thousands of iterations to guarantee high sample quality, which poses a challenge for accelerating sampling.
https://github.com/Rongjiehuang/ProDiff

Text2Light: Zero-Shot Text-Driven HDR Panorama Generation

📝To achieve super-resolution inverse tone mapping, we derive a continuous representation of 360-degree imaging from the LDR panorama as a set of structured latent codes anchored to the sphere.

https://github.com/frozenburning/text2light

SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

📝Notably, SegNeXt outperforms EfficientNet-L2 w/ NAS-FPN and achieves 90. 6% mIoU on the Pascal VOC 2012 test leaderboard using only 1/10 parameters of it.

https://github.com/visual-attention-network/segnext

Robust Speech Recognition via Large-Scale Weak Supervision

📝We study the capabilities of speech processing systems trained simply to predict large amounts of transcripts of audio on the internet.

https://github.com/openai/whisper

Diffusion Models: A Comprehensive Survey of Methods and Applications

📝Diffusion models are a class of deep generative models that have shown impressive results on various tasks with a solid theoretical foundation.

https://github.com/YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy

Plenoxels: Radiance Fields without Neural Networks

📝We introduce Plenoxels (plenoptic voxels), a system for photorealistic view synthesis.

https://github.com/kakaobrain/NeRF-Factory

LAVIS: A Library for Language-Vision Intelligence

📝We introduce LAVIS, an open-source deep learning library for LAnguage-VISion research and applications.

https://github.com/salesforce/lavis

DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

📝Compared to other models on the leaderboard, DINO significantly reduces its model size and pre-training data size while achieving better results.

https://github.com/IDEA-Research/detrex

Deep Learning for Medical Image Segmentation: Tricks, Challenges and Future Directions

📝Over the past few years, the rapid development of deep learning technologies for computer vision has greatly promoted the performance of medical image segmentation (MedISeg).

https://github.com/hust-linyi/seg_trick

High-Resolution Image Synthesis with Latent Diffusion Models

📝By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond.

https://github.com/compvis/stable-diffusion

USB: A Unified Semi-supervised Learning Benchmark

📝Semi-supervised learning (SSL) improves model generalization by leveraging massive unlabeled data to augment limited labeled samples.

https://github.com/microsoft/semi-supervised-learning

Advancing Model Pruning via Bi-level Optimization

📝To reduce the computation overhead, various efficient 'one-shot' pruning methods have been developed, but these schemes are usually unable to find winning tickets as good as IMP.

https://github.com/optml-group/bip

An Efficient Person Clustering Algorithm for Open Checkout-free Groceries

📝Then, to ensure that the method adapts to the dynamic and unseen person flow, we propose Graph Convolutional Network (GCN) with a simple Nearest Neighbor (NN) strategy to accurately cluster the instances of CSG.

https://github.com/WuJunde/checkoutfree

NerfAcc: A General NeRF Acceleration Toolbox

📝We propose NerfAcc, a toolbox for efficient volumetric rendering of radiance fields.
https://github.com/kair-bair/nerfacc

Human Motion Diffusion Model

📝In this paper, we introduce Motion Diffusion Model (MDM), a carefully adapted classifier-free diffusion-based generative model for the human motion domain.
https://github.com/guytevet/motion-diffusion-model

VToonify: Controllable High-Resolution Portrait Video Style Transfer

📝Although a series of successful portrait image toonification models built upon the powerful StyleGAN have been proposed, these image-oriented methods have obvious limitations when applied to videos, such as the fixed frame size, the requirement of face alignment, missing non-facial details and temporal inconsistency.
https://github.com/williamyang1991/vtoonify