✒️ Reweighting Strategy based on Synthetic Data Identification for Sentence Similarity
novel approach that first trains the classifier to measure the importance of each sentence
Github: https://github.com/ddehun/coling2022_reweighting_sts
Paper: https://arxiv.org/abs/2208.13376v2
Dataset: https://paperswithcode.com/dataset/mrpc
@ArtificialIntelligencedl
novel approach that first trains the classifier to measure the importance of each sentence
Github: https://github.com/ddehun/coling2022_reweighting_sts
Paper: https://arxiv.org/abs/2208.13376v2
Dataset: https://paperswithcode.com/dataset/mrpc
@ArtificialIntelligencedl
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👨 Controllable 3D Generative Adversarial Face Model via Disentangling Shape and Appearance
Github: https://github.com/aashishrai3799/3DFaceCAM
Project: https://aashishrai3799.github.io/3DFaceCAM
Paper: https://arxiv.org/abs/2208.14263
Video: https://drive.google.com/file/d/1PqIN4Rzp4vapWs2pUegUEoMhg4lM2Smy/view?usp=sharing
Dataset: https://paperswithcode.com/dataset/facescape
@ArtificialIntelligencedl
Github: https://github.com/aashishrai3799/3DFaceCAM
Project: https://aashishrai3799.github.io/3DFaceCAM
Paper: https://arxiv.org/abs/2208.14263
Video: https://drive.google.com/file/d/1PqIN4Rzp4vapWs2pUegUEoMhg4lM2Smy/view?usp=sharing
Dataset: https://paperswithcode.com/dataset/facescape
@ArtificialIntelligencedl
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🏙 AccoMontage2: A Complete Harmonization and Accompaniment Arrangement System
Github: https://github.com/billyblu2000/accomontage2
Paper: https://arxiv.org/abs/2209.00353v1
Dataset: https://drive.google.com/drive/folders/1z8oW16dZtdS06woHc7_rxserNJRrkc4s?usp=sharing
@ArtificialIntelligencedl
Github: https://github.com/billyblu2000/accomontage2
Paper: https://arxiv.org/abs/2209.00353v1
Dataset: https://drive.google.com/drive/folders/1z8oW16dZtdS06woHc7_rxserNJRrkc4s?usp=sharing
@ArtificialIntelligencedl
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💫 AccoMontage2: A Complete Harmonization and Accompaniment Arrangement System
AccoMontage2, a system capable of doing full-length song harmonization and accompaniment arrangement based on a lead melod
Github: https://github.com/billyblu2000/accomontage2
Paper: https://arxiv.org/abs/2209.00353v1
Dataset: https://drive.google.com/drive/folders/1z8oW16dZtdS06woHc7_rxserNJRrkc4s?usp=sharing
@ArtificialIntelligencedl
AccoMontage2, a system capable of doing full-length song harmonization and accompaniment arrangement based on a lead melod
Github: https://github.com/billyblu2000/accomontage2
Paper: https://arxiv.org/abs/2209.00353v1
Dataset: https://drive.google.com/drive/folders/1z8oW16dZtdS06woHc7_rxserNJRrkc4s?usp=sharing
@ArtificialIntelligencedl
❤7👍3
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🔘 Real-time 3D Single Object Tracking with Transformer
Github: https://github.com/shanjiayao/ptt
Paper: https://arxiv.org/abs/2209.00860v1
Dataset: https://paperswithcode.com/dataset/kitti
Video: https://youtu.be/Cajj6iHFvrc
@ArtificialIntelligencedl
Github: https://github.com/shanjiayao/ptt
Paper: https://arxiv.org/abs/2209.00860v1
Dataset: https://paperswithcode.com/dataset/kitti
Video: https://youtu.be/Cajj6iHFvrc
@ArtificialIntelligencedl
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📍 Structural Bias for Aspect Sentiment Triplet Extraction
Github: https://github.com/genezc/structbias
Paper: https://arxiv.org/abs/2209.00820v1
@ArtificialIntelligencedl
Github: https://github.com/genezc/structbias
Paper: https://arxiv.org/abs/2209.00820v1
@ArtificialIntelligencedl
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⚡️ Continual Learning: Fast and Slow
Dual Networks a general continual learning framework comprising a fast learning system for supervised learning of pattern-separated representation.
Github: https://github.com/phquang/DualNet
Paper: https://arxiv.org/abs/2209.02370v1
Dataset: https://paperswithcode.com/dataset/svhn
@ArtificialIntelligencedl
Dual Networks a general continual learning framework comprising a fast learning system for supervised learning of pattern-separated representation.
Github: https://github.com/phquang/DualNet
Paper: https://arxiv.org/abs/2209.02370v1
Dataset: https://paperswithcode.com/dataset/svhn
@ArtificialIntelligencedl
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🧠 Morphology-preserving Autoregressive 3D Generative Modelling of the Brain
Github: https://github.com/amigolab/synthanatomy
Paper: https://arxiv.org/abs/2209.03177v1
Project: http://amigos.ai/thisbraindoesnotexist/
@ArtificialIntelligencedl
Github: https://github.com/amigolab/synthanatomy
Paper: https://arxiv.org/abs/2209.03177v1
Project: http://amigos.ai/thisbraindoesnotexist/
@ArtificialIntelligencedl
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Forwarded from Machinelearning
🔥 YOLOv6
YOLOv6-N hits 35.9% AP on COCO dataset with 1234 FPS on T4. YOLOv6-S strikes 43.5% AP with 495 FPS, and the quantized YOLOv6-S model achieves 43.3% AP at a accelerated speed of 869 FPS on T4.
git clone https://github.com/meituan/YOLOv6
cd YOLOv6
pip install -r requirements.txt
⚙️ Github
➡️ Paper
✔️ Colab
💻 Quantization Tutorial
📄 Dataset
@ai_machinelearning_big_data
YOLOv6-N hits 35.9% AP on COCO dataset with 1234 FPS on T4. YOLOv6-S strikes 43.5% AP with 495 FPS, and the quantized YOLOv6-S model achieves 43.3% AP at a accelerated speed of 869 FPS on T4.
git clone https://github.com/meituan/YOLOv6
cd YOLOv6
pip install -r requirements.txt
⚙️ Github
➡️ Paper
✔️ Colab
💻 Quantization Tutorial
📄 Dataset
@ai_machinelearning_big_data
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💬 Text-Free Learning of a Natural Language Interface for Pretrained Face Generators
Fast text2StyleGAN, a natural language interface that adapts pre-trained GANs for text-guided human face synthesis.
pip install git+https://github.com/openai/CLIP.git
Github: https://github.com/duxiaodan/fast_text2stylegan
Paper: https://arxiv.org/abs/2209.03177v1
Dataset: https://paperswithcode.com/dataset/ffhq
@ArtificialIntelligencedl
Fast text2StyleGAN, a natural language interface that adapts pre-trained GANs for text-guided human face synthesis.
pip install git+https://github.com/openai/CLIP.git
Github: https://github.com/duxiaodan/fast_text2stylegan
Paper: https://arxiv.org/abs/2209.03177v1
Dataset: https://paperswithcode.com/dataset/ffhq
@ArtificialIntelligencedl
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💬 AARGH! End-to-end Retrieval-Generation for Task-Oriented Dialog
git clone https://github.com/Tomiinek/Aargh.git
cd Aargh
pip install -e .
Github: https://github.com/tomiinek/aargh
Paper: https://arxiv.org/abs/2209.03632v1
Dataset: https://paperswithcode.com/dataset/multiwoz
@ArtificialIntelligencedl
git clone https://github.com/Tomiinek/Aargh.git
cd Aargh
pip install -e .
Github: https://github.com/tomiinek/aargh
Paper: https://arxiv.org/abs/2209.03632v1
Dataset: https://paperswithcode.com/dataset/multiwoz
@ArtificialIntelligencedl
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🔭 AiRLoc: Aerial View Goal Localization with Reinforcement Learning
conda create -n airloc
conda activate airloc
pip install -r requirements.txt
Github: https://github.com/aleksispi/airloc
Paper: https://arxiv.org/abs/2209.03694v1
@ArtificialIntelligencedl
conda create -n airloc
conda activate airloc
pip install -r requirements.txt
Github: https://github.com/aleksispi/airloc
Paper: https://arxiv.org/abs/2209.03694v1
@ArtificialIntelligencedl
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MassMIND: Massachusetts Maritime INfrared Dataset 1
Github: https://github.com/uml-marine-robotics/massmind
Paper: https://arxiv.org/abs/2209.04097v1
Dataset: https://drive.google.com/file/d/1T572f0oqy5JmuTvVEwkSUeXLWOSHl4hL/view
@ArtificialIntelligencedl
Github: https://github.com/uml-marine-robotics/massmind
Paper: https://arxiv.org/abs/2209.04097v1
Dataset: https://drive.google.com/file/d/1T572f0oqy5JmuTvVEwkSUeXLWOSHl4hL/view
@ArtificialIntelligencedl
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💫 F-COREF: Fast, Accurate and Easy to Use Coreference Resolution
a python package for fast, accurate, and easy-to-use English coreference resolution.
Github: https://github.com/shon-otmazgin/fastcoref
Paper: https://arxiv.org/abs/2209.04280v2
Dataset: https://paperswithcode.com/dataset/multi-news
@ArtificialIntelligencedl
a python package for fast, accurate, and easy-to-use English coreference resolution.
pip install fastcorefGithub: https://github.com/shon-otmazgin/fastcoref
Paper: https://arxiv.org/abs/2209.04280v2
Dataset: https://paperswithcode.com/dataset/multi-news
@ArtificialIntelligencedl
👍4
🦾 StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation
Github: https://github.com/adymaharana/storydalle
Paper: https://arxiv.org/abs/2209.06192
Model: https://github.com/adymaharana/storydalle/blob/main/MODEL_CARD.MD
Demo: https://github.com/adymaharana/storydalle/blob/main/DEMO.MD
Dataset: https://paperswithcode.com/dataset/multi-news
@ArtificialIntelligencedl
Github: https://github.com/adymaharana/storydalle
Paper: https://arxiv.org/abs/2209.06192
Model: https://github.com/adymaharana/storydalle/blob/main/MODEL_CARD.MD
Demo: https://github.com/adymaharana/storydalle/blob/main/DEMO.MD
Dataset: https://paperswithcode.com/dataset/multi-news
@ArtificialIntelligencedl
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🚀 Entity Tagging: Extracting Entities in Text Without Mention Supervision
Github: https://github.com/facebookresearch/groov
Paper: https://arxiv.org/abs/2209.06148v1
Model: https://github.com/adymaharana/storydalle/blob/main/MODEL_CARD.MD
Dataset: http://manikvarma.org/downloads/XC/XMLRepository.html
@ArtificialIntelligencedl
Github: https://github.com/facebookresearch/groov
Paper: https://arxiv.org/abs/2209.06148v1
Model: https://github.com/adymaharana/storydalle/blob/main/MODEL_CARD.MD
Dataset: http://manikvarma.org/downloads/XC/XMLRepository.html
@ArtificialIntelligencedl
👍6
🛠 CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Representation Alignment
Github: https://github.com/microsoft/xpretrain
Paper: https://arxiv.org/abs/2209.06430v1
Dataset: https://paperswithcode.com/dataset/flickr30k
@ArtificialIntelligencedl
Github: https://github.com/microsoft/xpretrain
Paper: https://arxiv.org/abs/2209.06430v1
Dataset: https://paperswithcode.com/dataset/flickr30k
@ArtificialIntelligencedl
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📲 Self-distilled Feature Aggregation for Self-supervised Monocular Depth Estimation
Github: https://github.com/ZM-Zhou/SMDE-Pytorch
Paper: https://arxiv.org/abs/2209.07088v1
Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
Github: https://github.com/ZM-Zhou/SMDE-Pytorch
Paper: https://arxiv.org/abs/2209.07088v1
Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
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🛠 Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer?
⚙️Github: https://github.com/VITA-Group/Simple3D-Former
📄Paper: https://arxiv.org/abs/2209.07026v1
📎Dataset: https://paperswithcode.com/dataset/modelnet
@ArtificialIntelligencedl
⚙️Github: https://github.com/VITA-Group/Simple3D-Former
📄Paper: https://arxiv.org/abs/2209.07026v1
📎Dataset: https://paperswithcode.com/dataset/modelnet
@ArtificialIntelligencedl
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🖊 Causes of Catastrophic Forgetting in Class-Incremental Semantic Segmentation
Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.
⚙️Github: https://github.com/mmasana/FACIL
📄Paper: https://arxiv.org/abs/2209.08010v1
📎Dataset: https://github.com/mmasana/FACIL/blob/master/src/datasets#datasets
@ArtificialIntelligencedl
Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.
git clone https://github.com/mmasana/FACIL.git
cd FACIL⚙️Github: https://github.com/mmasana/FACIL
📄Paper: https://arxiv.org/abs/2209.08010v1
📎Dataset: https://github.com/mmasana/FACIL/blob/master/src/datasets#datasets
@ArtificialIntelligencedl
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🔌 HiPart: Hierarchical divisive clustering toolbox
It is a package with similar execution principles as the scikit-learn package. It also provides two types of static visualizations for all the algorithms executed in the package, with the addition of linkage generation for the divisive hierarchical clustering structure.
⚙️Github: https://github.com/panagiotisanagnostou/hipart
📄Paper: https://arxiv.org/abs/2209.08680v1
📎Dataset: https://paperswithcode.com/dataset/usps
@ArtificialIntelligencedl
It is a package with similar execution principles as the scikit-learn package. It also provides two types of static visualizations for all the algorithms executed in the package, with the addition of linkage generation for the divisive hierarchical clustering structure.
pip install HiPart⚙️Github: https://github.com/panagiotisanagnostou/hipart
📄Paper: https://arxiv.org/abs/2209.08680v1
📎Dataset: https://paperswithcode.com/dataset/usps
@ArtificialIntelligencedl
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