Group R-CNN for Point-based Weakly Semi-supervised Object Detection
Code: https://github.com/jshilong/grouprcnn
Paper: https://arxiv.org/abs/2205.05920v1
Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
Code: https://github.com/jshilong/grouprcnn
Paper: https://arxiv.org/abs/2205.05920v1
Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
Real-Time Packet Loss Concealment With Mixed Generative and Predictive Model
Low complexity implementation of the WaveRNN-based LPCNet algorithm
Github: https://github.com/xiph/lpcnet
Paper: https://arxiv.org/abs/2205.05785v1
OpenSLR: https://www.openslr.org/
@ArtificialIntelligencedl
Low complexity implementation of the WaveRNN-based LPCNet algorithm
Github: https://github.com/xiph/lpcnet
Paper: https://arxiv.org/abs/2205.05785v1
OpenSLR: https://www.openslr.org/
@ArtificialIntelligencedl
π5
π Automated Crossword Solving
Pretrained models, precomputed FAISS embeddings, and a crossword clue-answer dataset.
Github: https://github.com/albertkx/berkeley-crossword-solver
Paper: https://arxiv.org/abs/2205.09665v1
Dataset: https://www.xwordinfo.com/JSON/
Pretrained models, precomputed FAISS embeddings, and a crossword clue-answer dataset.
Github: https://github.com/albertkx/berkeley-crossword-solver
Paper: https://arxiv.org/abs/2205.09665v1
Dataset: https://www.xwordinfo.com/JSON/
π6π1
[RK-Net]Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization
Github: https://github.com/AggMan96/RK-Net
Paper: https://zhunzhong.site/paper/RK_Net.pdf
Dataset: https://paperswithcode.com/dataset/university-1652
@ArtificialIntelligencedl
Github: https://github.com/AggMan96/RK-Net
Paper: https://zhunzhong.site/paper/RK_Net.pdf
Dataset: https://paperswithcode.com/dataset/university-1652
@ArtificialIntelligencedl
π5
AdaVAE: Exploring Adaptive GPT-2s in Variational Auto-Encoders for Language Modeling
First VAE framework empowered with adaptive GPT-2s (AdaVAE).
Github: https://github.com/ImKeTT/adavae
Paper: https://arxiv.org/abs/2205.05862v1
Task: https://paperswithcode.com/task/representation-learning
@ArtificialIntelligencedl
First VAE framework empowered with adaptive GPT-2s (AdaVAE).
Github: https://github.com/ImKeTT/adavae
Paper: https://arxiv.org/abs/2205.05862v1
Task: https://paperswithcode.com/task/representation-learning
@ArtificialIntelligencedl
π6
KG-SP: Knowledge Guided Simple Primitives for Open World Compositional Zero-Shot Learning
Github: https://github.com/explainableml/kg-sp
Paper: https://arxiv.org/abs/2205.06784v1
Dataset: https://paperswithcode.com/dataset/conceptnet
@ArtificialIntelligencedl
Github: https://github.com/explainableml/kg-sp
Paper: https://arxiv.org/abs/2205.06784v1
Dataset: https://paperswithcode.com/dataset/conceptnet
@ArtificialIntelligencedl
Experiments on Generalizability of User-Oriented Fairness in Recommender Systems.
Github: https://github.com/rahmanidashti/fairrecsys
Paper: https://arxiv.org/abs/2205.08289v1
Dataset: https://paperswithcode.com/dataset/movielens
@ArtificialIntelligencedl
Github: https://github.com/rahmanidashti/fairrecsys
Paper: https://arxiv.org/abs/2205.08289v1
Dataset: https://paperswithcode.com/dataset/movielens
@ArtificialIntelligencedl
Towards Unified Keyframe Propagation Models
A two-stream approach, where high-frequency features interact locally and low-frequency features interact globally.
Github: https://github.com/runwayml/guided-inpainting
Paper: https://arxiv.org/abs/2205.09731v1
Dataset: https://paperswithcode.com/dataset/places
@ArtificialIntelligencedl
A two-stream approach, where high-frequency features interact locally and low-frequency features interact globally.
Github: https://github.com/runwayml/guided-inpainting
Paper: https://arxiv.org/abs/2205.09731v1
Dataset: https://paperswithcode.com/dataset/places
@ArtificialIntelligencedl
π5
π A graph-transformer for whole slide image classification
Graph-Transformer (GT) that fuses a graph-based representation of an WSI and a vision transformer for processing pathology images.
Github: https://github.com/vkola-lab/tmi2022
Paper: https://arxiv.org/abs/2205.09671v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
Graph-Transformer (GT) that fuses a graph-based representation of an WSI and a vision transformer for processing pathology images.
Github: https://github.com/vkola-lab/tmi2022
Paper: https://arxiv.org/abs/2205.09671v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
π4
RankGen - Improving Text Generation with Large Ranking Models
RankGen is a 1.2 billion encoder model which maps prefixes and generations from any language model (in continutation to the prefix) to a shared vector space.
Github: https://github.com/martiansideofthemoon/rankgen
Paper: https://arxiv.org/abs/2205.09726
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
RankGen is a 1.2 billion encoder model which maps prefixes and generations from any language model (in continutation to the prefix) to a shared vector space.
Github: https://github.com/martiansideofthemoon/rankgen
Paper: https://arxiv.org/abs/2205.09726
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
π4
β‘οΈ Structured Attention Composition for Temporal Action Localization
Online action detection and effective and efficient exemplar-consultation mechanism
Github: https://github.com/vividle/online-action-detection
Paper: https://arxiv.org/abs/2205.09956v1
Dataset: https://paperswithcode.com/dataset/places
@ArtificialIntelligencedl
Online action detection and effective and efficient exemplar-consultation mechanism
Github: https://github.com/vividle/online-action-detection
Paper: https://arxiv.org/abs/2205.09956v1
Dataset: https://paperswithcode.com/dataset/places
@ArtificialIntelligencedl
π2
Full camouflage fixation training dataset is available!
The full camouflage fixation training dataset is available with the full fixation maps for the COD10K training dataset, which can be downloaded from: https://drive.google.com/file/d/1inb5iNTDswFPDm4SpzBbVgZdI4puAv_3/view?usp=sharing
Github: https://github.com/JingZhang617/COD-Rank-Localize-and-Segment
Paper: https://arxiv.org/abs/2205.11333v1
Dataset: https://paperswithcode.com/dataset/salicon
@ArtificialIntelligencedl
The full camouflage fixation training dataset is available with the full fixation maps for the COD10K training dataset, which can be downloaded from: https://drive.google.com/file/d/1inb5iNTDswFPDm4SpzBbVgZdI4puAv_3/view?usp=sharing
Github: https://github.com/JingZhang617/COD-Rank-Localize-and-Segment
Paper: https://arxiv.org/abs/2205.11333v1
Dataset: https://paperswithcode.com/dataset/salicon
@ArtificialIntelligencedl
π3
ASSET: Autoregressive Semantic Scene Editing with Transformers at High Resolutions
Github: https://github.com/difanliu/asset
Paper: https://arxiv.org/abs/2205.12231v1
Dataset: https://paperswithcode.com/dataset/ade20k
Pretrained model: https://www.dropbox.com/s/5kyov71ko340ra0/landscape.zip?dl=0
@ArtificialIntelligencedl
Github: https://github.com/difanliu/asset
Paper: https://arxiv.org/abs/2205.12231v1
Dataset: https://paperswithcode.com/dataset/ade20k
Pretrained model: https://www.dropbox.com/s/5kyov71ko340ra0/landscape.zip?dl=0
@ArtificialIntelligencedl
π4
Recipe for a General, Powerful, Scalable Graph Transformer
Github: https://github.com/rampasek/GraphGPS
Paper: https://arxiv.org/abs/2205.12454v1
Dataset: https://paperswithcode.com/dataset/malnet
@ArtificialIntelligencedl
Github: https://github.com/rampasek/GraphGPS
Paper: https://arxiv.org/abs/2205.12454v1
Dataset: https://paperswithcode.com/dataset/malnet
@ArtificialIntelligencedl
π₯3
On the Eigenvalues of Global Covariance Pooling for Fine-grained Visual Recognition
Github: https://github.com/KingJamesSong/DifferentiableSVD
Paper: https://arxiv.org/abs/2205.13282v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
Github: https://github.com/KingJamesSong/DifferentiableSVD
Paper: https://arxiv.org/abs/2205.13282v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
π6
SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation
Github: https://github.com/wangzy22/SemAffiNet
Paper: https://arxiv.org/abs/2205.13490v1
Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
Github: https://github.com/wangzy22/SemAffiNet
Paper: https://arxiv.org/abs/2205.13490v1
Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
β€3π1
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CMA-ES with Margin
CMA-ES with Margin (CMA-ESwM) [1] is a CMA-ES variant proposed for mixed-integer black-box optimization, which introduces a lower bound on the marginal probability associated with integer variables.
Github: https://github.com/evoconjp/cma-es_with_margin
Paper: https://arxiv.org/abs/2205.13482v1
@ArtificialIntelligencedl
CMA-ES with Margin (CMA-ESwM) [1] is a CMA-ES variant proposed for mixed-integer black-box optimization, which introduces a lower bound on the marginal probability associated with integer variables.
Github: https://github.com/evoconjp/cma-es_with_margin
Paper: https://arxiv.org/abs/2205.13482v1
@ArtificialIntelligencedl
π5
π» BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework
Github: https://github.com/adlab-autodrive/bevfusion
Paper: https://arxiv.org/abs/2205.13790v1
Dataset: https://paperswithcode.com/dataset/kitti
@ArtificialIntelligencedl
Github: https://github.com/adlab-autodrive/bevfusion
Paper: https://arxiv.org/abs/2205.13790v1
Dataset: https://paperswithcode.com/dataset/kitti
@ArtificialIntelligencedl
π5
Surface Vision Transformers
Github: https://github.com/metrics-lab/surface-vision-transformers
Paper: https://arxiv.org/abs/2205.15836v1
@ArtificialIntelligencedl
Github: https://github.com/metrics-lab/surface-vision-transformers
Paper: https://arxiv.org/abs/2205.15836v1
@ArtificialIntelligencedl
β€4