Multi-instrument Music Synthesis with Spectrogram Diffusion

📝An ideal music synthesizer should be both interactive and expressive, generating high-fidelity audio in realtime for arbitrary combinations of instruments and notes.

https://github.com/magenta/music-spectrogram-diffusion

MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction
📝We adopt a hierarchical query embedding scheme to flexibly encode structured map information and perform hierarchical bipartite matching for map element learning.

https://github.com/hustvl/maptr

YOLOPv2: Better, Faster, Stronger for Panoptic Driving Perception

📝Over the last decade, multi-tasking learning approaches have achieved promising results in solving panoptic driving perception problems, providing both high-precision and high-efficiency performance.

https://github.com/CAIC-AD/YOLOPv2

Topology-aware Convolutional Neural Network for Efficient Skeleton-based Action Recognition

📝In particular, we develop a novel cross-channel feature augmentation module, which is a combo of map-attend-group-map operations.

https://github.com/hikvision-research/skelact

FILM: Frame Interpolation for Large Motion

📝Recent methods use multiple networks to estimate optical flow or depth and a separate network dedicated to frame synthesis.

https://github.com/google-research/frame-interpolation

Online Decision Transformer

📝Recent work has shown that offline reinforcement learning (RL) can be formulated as a sequence modeling problem (Chen et al., 2021; Janner et al., 2021) and solved via approaches similar to large-scale language modeling.

https://github.com/facebookresearch/online-dt

YOLOX-PAI: An Improved YOLOX Version by PAI

📝We develop an all-in-one computer vision toolbox named EasyCV to facilitate the use of various SOTA computer vision methods.

https://github.com/alibaba/EasyCV

PeRFception: Perception using Radiance Fields

📝The recent progress in implicit 3D representation, i. e., Neural Radiance Fields (NeRFs), has made accurate and photorealistic 3D reconstruction possible in a differentiable manner.

https://github.com/POSTECH-CVLab/PeRFception

DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation

📝Once the subject is embedded in the output domain of the model, the unique identifier can then be used to synthesize fully-novel photorealistic images of the subject contextualized in different scenes.

https://github.com/XavierXiao/Dreambooth-Stable-Diffusion

CLIP-Mesh: Generating textured meshes from text using pretrained image-text models

📝We present a technique for zero-shot generation of a 3D model using only a target text prompt.

https://github.com/NasirKhalid24/CLIP-Mesh

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