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CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
To enable evaluation of progress on code search, we are releasing the CodeSearchNet Corpus and are presenting the CodeSearchNet Challenge, which consists of 99 natural language queries with about 4k expert relevance annotations of likely results from CodeSearchNet Corpus.
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
hazyresearch/flash-attention
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We also extend FlashAttention to block-sparse attention, yielding an approximate attention algorithm that is faster than any existing approximate attention method.
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
MCG-NJU/VideoMAE
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Pre-training video transformers on extra large-scale datasets is generally required to achieve premier performance on relatively small datasets.
Matryoshka Representation Learning
raivnlab/mrl
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The flexibility within the learned Matryoshka Representations offer: (a) up to 14x smaller embedding size for ImageNet-1K classification at the same level of accuracy; (b) up to 14x real-world speed-ups for large-scale retrieval on ImageNet-1K and 4K; and (c) up to 2% accuracy improvements for long-tail few-shot classification, all while being as robust as the original representations.
Better Computer Go Player with Neural Network and Long-term Prediction
facebookresearch/darkforestGo
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Against human players, the newest versions, darkfores2, achieve a stable 3d level on KGS Go Server as a ranked bot, a substantial improvement upon the estimated 4k-5k ranks for DCNN reported in Clark & Storkey (2015) based on games against other machine players.
UAVid: A Semantic Segmentation Dataset for UAV Imagery
YeLyuUT/MSDNet
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There already exist several semantic segmentation datasets for comparison among semantic segmentation methods in complex urban scenes, such as the Cityscapes and CamVid datasets, where the side views of the objects are captured with a camera mounted on the driving car.
Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer
mousecpn/Joint-Bilateral-Learning
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ECCV 2020
Photorealistic style transfer is the task of transferring the artistic style of an image onto a content target, producing a result that is plausibly taken with a camera.
SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations
PaperCodeSubmission/AAAI2021-260
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Semi-supervised variational autoencoders (VAEs) have obtained strong results, but have also encountered the challenge that good ELBO values do not always imply accurate inference results.
Collapsible Linear Blocks for Super-Efficient Super Resolution
Our results highlight the challenges faced by super resolution on AI accelerators and demonstrate that SESR is significantly faster (e. g., 6x-8x higher FPS) than existing models on mobile-NPU.
NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
caiyuanhao1998/retinexformer
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This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.
