Trending Research
NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion
To cover language, image, and video at the same time for different scenarios, a 3D transformer encoder-decoder framework is designed, which can not only deal with videos as 3D data but also adapt to texts and images as 1D and 2D data, respectively.
MetaFormer is Actually What You Need for Vision
Based on this observation, we hypothesize that the general architecture of the transformers, instead of the specific token mixer module, is more essential to the model's performance.
Ranked #41 on
Semantic Segmentation
on ADE20K
Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation
We propose Prototypical Cross-Attention Network (PCAN), capable of leveraging rich spatio-temporal information for online multiple object tracking and segmentation.
Ranked #1 on
Multi-Object Tracking and Segmentation
on BDD100K
Multi-Object Tracking and Segmentation
Multiple Object Track and Segmentation
+1
Robust High-Resolution Video Matting with Temporal Guidance
PeterL1n/RobustVideoMatting
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We introduce a robust, real-time, high-resolution human video matting method that achieves new state-of-the-art performance.
Ranked #1 on
Video Matting
on VideoMatte240K
OpenUE: An Open Toolkit of Universal Extraction from Text
We introduce a prototype model and provide an open-source and extensible toolkit called OpenUE for various extraction tasks.
Resolution-robust Large Mask Inpainting with Fourier Convolutions
saic-mdal/lama
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We find that one of the main reasons for that is the lack of an effective receptive field in both the inpainting network and the loss function.
KML: Using Machine Learning to Improve Storage Systems
Operating systems include many heuristic algorithms designed to improve overall storage performance and throughput.
PaddleViT
BR-IDL/PaddleViT
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:robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2. 0+
PaddleRec
大规模推荐算法库，包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、DeepWalk、SSR、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESMM、MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、ListWise等，包含经典推荐系统数据集criteo 、movielens等
Masked Autoencoders Are Scalable Vision Learners
Our MAE approach is simple: we mask random patches of the input image and reconstruct the missing pixels.
Ranked #10 on
Semantic Segmentation
on ADE20K
