📌 Sparse Fusion Mixture-of-Experts are Domain Generalizable Learners

Sparse Fusion Mixture-of-Experts (SF-MoE), which incorporates sparsity and fusion mechanisms into the MoE framework to keep the model both sparse and predictive.

Github: https://github.com/luodian/sf-moe-dg

Paper: https://arxiv.org/abs/2206.04046v1

Documentation: https://paperswithcode.com/dataset/domainnet

@ArtificialIntelligencedl

🔹 PointNeXt & OpenPoints Library

improved training and model scaling strategies to boost PointNet++ to the state-of-the-art level.

Github: https://github.com/guochengqian/pointnext

Paper: https://paperswithcode.com/dataset/shapenet

@ArtificialIntelligencedl

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Github: https://github.com/google/BIG-bench

Paper: https://arxiv.org/abs/2206.04615v1

Dataset: https://paperswithcode.com/dataset/glue

@ArtificialIntelligencedl

Revisiting End-to-End Speech-to-Text Translation From Scratch

Github: https://github.com/bzhangGo/zero

Paper: https://arxiv.org/abs/2206.04571v1

Dataset: https://paperswithcode.com/dataset/must-c

@ArtificialIntelligencedl

🔊 SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning

We introduce SoundSpaces 2.0, a platform for on-the-fly geometry-based audio rendering for 3D environments.

Github: https://github.com/facebookresearch/sound-spaces

Paper: https://arxiv.org/abs/2206.08312v1

Dataset: https://paperswithcode.com/dataset/librispeech

Meta Optimal Transport

Github: https://github.com/facebookresearch/meta-ot

Paper: https://arxiv.org/abs/2206.05262v1



@ArtificialIntelligencedl

🔦 Featurized Query R-CNN

Featurized object queries predicted by a query generation network in the well-established Faster R-CNN framework and develop a Featurized Query R-CN

Github: https://github.com/hustvl/featurized-queryrcnn

Paper: https://arxiv.org/abs/2206.06258v1

Dataset: https://paperswithcode.com/dataset/crowdhuman

@ArtificialIntelligencedl

UniSRec

The proposed approach utilizes the associated description text of items to learn transferable representations across different recommendation scenarios.

Github: https://github.com/rucaibox/unisrec

Paper: https://arxiv.org/abs/2206.05941v1

Google Drive: https://drive.google.com/drive/folders/1Uik0fMk4oquV_bS9lXTZuExAYbIDkEMW?usp=sharing

@ArtificialIntelligencedl

🌑 LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection

Waymo Open Dataset publicly to aid the research community in making advancements in machine perception and autonomous driving technology.

Github: https://github.com/waymo-research/waymo-open-dataset

Paper: https://arxiv.org/abs/2206.07705v1

Dataset: https://paperswithcode.com/dataset/waymo-open-datasetg

@ArtificialIntelligencedl

🖊 StrengthNet

Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

Github: https://github.com/ttslr/strengthnet

Paper: https://arxiv.org/abs/2110.03156

MOSNet: https://github.com/lochenchou/MOSNet

@ai_machinelearning_big_data

DeepFormableTag: End-to-end Generation and Recognition of Deformable Fiducial Markers

Github: https://github.com/KAIST-VCLAB/DeepFormableTag

Project: https://vclab.kaist.ac.kr/siggraph2021/index.html

Paper: https://vclab.kaist.ac.kr/siggraph2021/DeepFormableTag-main-screen.pdf

Dataset: https://drive.google.com/drive/folders/1picphIb6Hbj6pM3Wu_Vxu53wzKBV0jdV

@ArtificialIntelligencedl

🏙 Spatially-Adapive Multilayer (SAM) Inversion

Proposed method automatically selects the latent space tailored for each region to balance the reconstruction quality and editability (3rd row).

Github: https://github.com/adobe-research/sam_inversion

Project: https://www.cs.cmu.edu/~SAMInversion/

Paper: https://arxiv.org/abs/2206.08357

@ArtificialIntelligencedl

Automatic Prosody Annotation with Pre-Trained Text-Speech Model

Github: https://github.com/daisyqk/automatic-prosody-annotation

Project: https://daisyqk.github.io/Automatic-Prosody-Annotation_w/

Paper: https://arxiv.org/abs/2206.07956v1

@ArtificialIntelligencedl

🦾 Bi-DexHands: Bimanual Dexterous Manipulation via Reinforcement Learning

Bi-DexHands provides a collection of bimanual dexterous manipulations tasks and reinforcement learning algorithms.

Github: https://github.com/pku-marl/dexteroushands

Isaac Gym: https://developer.nvidia.com/isaac-gym

Paper: hhttps://arxiv.org/abs/2206.08686

@ArtificialIntelligencedl

🕹 SENSORIUM 2022 Competition

The Sensorium competition on predicting large-scale mouse primary visual cortex activity

Github: https://github.com/sinzlab/sensorium

Website: https://sensorium2022.net/

Paper: https://arxiv.org/abs/2206.08666v1

@ArtificialIntelligencedl

🔎 Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping

Github:https://github.com/airlab-polimi/c-slam

Tutorial: https://ros.org/wiki/catkin/Tutorials/create_a_workspace

Paper: https://arxiv.org/abs/2206.10263v1

@ArtificialIntelligencedl

🧠 Identifying and Combating Bias in Segmentation Networks by leveraging multiple resolutions

Github: https://github.com/Deep-MI/FastSurfer

Colab: https://colab.research.google.com/github/Deep-MI/FastSurfer/blob/master/Tutorial/Tutorial_FastSurferCNN_QuickSeg.ipynb

Paper: https://arxiv.org/abs/2206.14919v1

🌩 Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping

PyGOD is a Python library for graph outlier detection (anomaly detection).

Github: https://github.com/pygod-team/pygod

Dataset : https://paperswithcode.com/dataset/ogb

Paper: https://arxiv.org/abs/2206.10071v1

@ArtificialIntelligencedl

💻 DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation

DaisyRec-v2.0 is a Python toolkit developed for benchmarking top-N recommendation task.

Github: https://github.com/recsys-benchmark/daisyrec-v2.0

Command Generator : https://daisyrecguicommandgenerator.pythonanywhere.com/

Paper: https://arxiv.org/abs/2206.10848v1

Tutorial: https://github.com/recsys-benchmark/DaisyRec-v2.0/blob/main/DaisyRec-v2.0-Tutorial.ipynb

@ArtificialIntelligencedl

Frequency Dynamic Convolution-Recurrent Neural Network (FDY-CRNN) for Sound Event Detection

Frequency Dynamic Convolution applied kernel that adapts to each freqeuncy bin of input, in order to remove tranlation equivariance of 2D convolution along the frequency axis.

Github: https://github.com/frednam93/FDY-SED

Paper: https://arxiv.org/abs/2206.11645v1

Dataset: https://paperswithcode.com/dataset/desed

@ArtificialIntelligencedl