Superpixel-based Refinement for Object Proposal Generation
Github: https://github.com/chwilms/superpixelRefinement
Paper: https://arxiv.org/abs/2101.04574v1
@ArtificialIntelligencedl
Github: https://github.com/chwilms/superpixelRefinement
Paper: https://arxiv.org/abs/2101.04574v1
@ArtificialIntelligencedl
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
Github: https://github.com/naver-ai/relabel_imagenet
Paper: https://arxiv.org/abs/2101.05022v1
@ArtificialIntelligencedl
Github: https://github.com/naver-ai/relabel_imagenet
Paper: https://arxiv.org/abs/2101.05022v1
@ArtificialIntelligencedl
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation
Github: https://github.com/huawei-noah/noah-research
Paper: https://arxiv.org/abs/2101.04849v1
@ArtificialIntelligencedl
Github: https://github.com/huawei-noah/noah-research
Paper: https://arxiv.org/abs/2101.04849v1
@ArtificialIntelligencedl
Computer Architecture-Aware Optimisation of DNA Analysis Systems
Github: https://github.com/hasindu2008/f5c
Paper: https://arxiv.org/abs/2101.05012v1
Full Documentation : https://hasindu2008.github.io/f5c/docs/overview
@ArtificialIntelligencedl
Github: https://github.com/hasindu2008/f5c
Paper: https://arxiv.org/abs/2101.05012v1
Full Documentation : https://hasindu2008.github.io/f5c/docs/overview
@ArtificialIntelligencedl
Temporal-Relational CrossTransformers for Few-Shot Action Recognition
Github: https://github.com/tobyperrett/trx
Paper: https://arxiv.org/abs/2101.06184v1
@ArtificialIntelligencedl
Github: https://github.com/tobyperrett/trx
Paper: https://arxiv.org/abs/2101.06184v1
@ArtificialIntelligencedl
Free Lunch for Few-shot Learning: Distribution Calibration
Github: https://github.com/ShuoYang-1998/ICLR2021-Oral_Distribution_Calibration
Paper: https://openreview.net/forum?id=JWOiYxMG92s
@ArtificialIntelligencedl
Github: https://github.com/ShuoYang-1998/ICLR2021-Oral_Distribution_Calibration
Paper: https://openreview.net/forum?id=JWOiYxMG92s
@ArtificialIntelligencedl
Momentum^2 Teacher: Momentum Teacher with Momentum Statistics for Self-Supervised Learning
Github: https://github.com/zengarden/momentum2-teacher
Paper: https://arxiv.org/abs/2101.07525v1
@ArtificialIntelligencedl
Github: https://github.com/zengarden/momentum2-teacher
Paper: https://arxiv.org/abs/2101.07525v1
@ArtificialIntelligencedl
Animesion
DAF:RE: A CHALLENGING, CROWD-SOURCED, LARGE-SCALE, LONG-TAILED
DATASET FOR ANIME CHARACTER RECOGNITION
Code:https://github.com/arkel23/animesion
Paper: https://arxiv.org/abs/2101.08674v1
@ArtificialIntelligencedl
DAF:RE: A CHALLENGING, CROWD-SOURCED, LARGE-SCALE, LONG-TAILED
DATASET FOR ANIME CHARACTER RECOGNITION
Code:https://github.com/arkel23/animesion
Paper: https://arxiv.org/abs/2101.08674v1
@ArtificialIntelligencedl
Self-Adaptive Training
Github: https://github.com/LayneH/self-adaptive-training
Paper: https://arxiv.org/abs/2101.08732v1
@ArtificialIntelligencedl
Github: https://github.com/LayneH/self-adaptive-training
Paper: https://arxiv.org/abs/2101.08732v1
@ArtificialIntelligencedl
The Ultimate Scikit-Learn Machine Learning Cheatsheet
https://www.kdnuggets.com/2021/01/ultimate-scikit-learn-machine-learning-cheatsheet.html
@ArtificialIntelligencedl
https://www.kdnuggets.com/2021/01/ultimate-scikit-learn-machine-learning-cheatsheet.html
@ArtificialIntelligencedl
Supervision by Registration and Triangulation for Landmark Detection
Github: https://github.com/D-X-Y/landmark-detection
Paper: https://arxiv.org/abs/2101.09866v1
@ArtificialIntelligencedl
Github: https://github.com/D-X-Y/landmark-detection
Paper: https://arxiv.org/abs/2101.09866v1
@ArtificialIntelligencedl
Summarising Historical Text in Modern Languages
Github: https://github.com/Pzoom522/HistSumm
Paper: https://arxiv.org/abs/2101.10759v2
@ArtificialIntelligencedl
Github: https://github.com/Pzoom522/HistSumm
Paper: https://arxiv.org/abs/2101.10759v2
@ArtificialIntelligencedl
Generalising via Meta-Examples for Continual Learning in the Wild
Github: https://github.com/alessiabertugli/FUSION
Article: https://arxiv.org/abs/2101.12081v1
@ArtificialIntelligencedl
Github: https://github.com/alessiabertugli/FUSION
Article: https://arxiv.org/abs/2101.12081v1
@ArtificialIntelligencedl
Playable Video Generation
Github: https://github.com/willi-menapace/PlayableVideoGeneration
Paper: https://arxiv.org/abs/2101.12195
@ArtificialIntelligencedl
Github: https://github.com/willi-menapace/PlayableVideoGeneration
Paper: https://arxiv.org/abs/2101.12195
@ArtificialIntelligencedl
Hands-on Guide to OpenAI’s CLIP – Connecting Text To Images
https://analyticsindiamag.com/hands-on-guide-to-openais-clip-connecting-text-to-images/
@ArtificialIntelligencedl
https://analyticsindiamag.com/hands-on-guide-to-openais-clip-connecting-text-to-images/
@ArtificialIntelligencedl
Saving and loading models in TensorFlow — why it is important and how to do it
https://www.kdnuggets.com/2021/02/saving-loading-models-tensorflow.html
@ArtificialIntelligencedl
https://www.kdnuggets.com/2021/02/saving-loading-models-tensorflow.html
@ArtificialIntelligencedl
KDnuggets
Saving and loading models in TensorFlow — why it is important and how to do it
So much time and effort can go into training your machine learning models. But, shut down the notebook or system, and all those trained weights and more vanish with the memory flush. Saving your models to maximize reusability is key for efficient productivity.
Spectral Leakage and Rethinking the Kernel Size in CNNs
Github: https://github.com/EvgenyKashin/non-leaking-conv
Paper: https://arxiv.org/abs/2101.10143
Notebook: https://github.com/EvgenyKashin/non-leaking-conv/blob/master/LearnedKernelsEDA.ipynb
@ArtificialIntelligencedl
Github: https://github.com/EvgenyKashin/non-leaking-conv
Paper: https://arxiv.org/abs/2101.10143
Notebook: https://github.com/EvgenyKashin/non-leaking-conv/blob/master/LearnedKernelsEDA.ipynb
@ArtificialIntelligencedl
Cleora: A Simple, Strong and Scalable Graph Embedding Scheme
Github: https://github.com/Synerise/cleora
Paper: https://arxiv.org/abs/2102.02302v1
@ArtificialIntelligencedl
Github: https://github.com/Synerise/cleora
Paper: https://arxiv.org/abs/2102.02302v1
@ArtificialIntelligencedl
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency
Github: https://github.com/SeokjuLee/Insta-DM
Paper: https://arxiv.org/abs/2102.02629v1
@ArtificialIntelligencedl
Github: https://github.com/SeokjuLee/Insta-DM
Paper: https://arxiv.org/abs/2102.02629v1
@ArtificialIntelligencedl