Trending Research
Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling
keyu-tian/spark
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This is the first use of sparse convolution for 2D masked modeling.
Ranked #1 on
Instance Segmentation
on COCO 2017 val
OCR-free Document Understanding Transformer
clovaai/donut
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Current Visual Document Understanding (VDU) methods outsource the task of reading text to off-the-shelf Optical Character Recognition (OCR) engines and focus on the understanding task with the OCR outputs.
Towards Robust Blind Face Restoration with Codebook Lookup Transformer
In this paper, we demonstrate that a learned discrete codebook prior in a small proxy space largely reduces the uncertainty and ambiguity of restoration mapping by casting blind face restoration as a code prediction task, while providing rich visual atoms for generating high-quality faces.
Ranked #1 on
Blind Face Restoration
on WIDER
DAMO-YOLO : A Report on Real-Time Object Detection Design
In this report, we present a fast and accurate object detection method dubbed DAMO-YOLO, which achieves higher performance than the state-of-the-art YOLO series.
Ranked #12 on
Real-Time Object Detection
on COCO
Multi-scale Multi-band DenseNets for Audio Source Separation
Anjok07/ultimatevocalremovergui
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This paper deals with the problem of audio source separation.
TorchGeo: Deep Learning With Geospatial Data
Deep learning methods are particularly promising for modeling many remote sensing tasks given the success of deep neural networks in similar computer vision tasks and the sheer volume of remotely sensed imagery available.
Planar Object Tracking via Weighted Optical Flow
serycjon/WOFT
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We propose WOFT -- a novel method for planar object tracking that estimates a full 8 degrees-of-freedom pose, i. e. the homography w. r. t.
On the Expressive Power of Geometric Graph Neural Networks
chaitjo/geometric-gnn-dojo
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The expressive power of Graph Neural Networks (GNNs) has been studied extensively through the Weisfeiler-Leman (WL) graph isomorphism test.
Utilizing supervised models to infer consensus labels and their quality from data with multiple annotators
Many algorithms also rely solely on annotator statistics, ignoring the features of the examples from which the annotations derive.
GLIGEN: Open-Set Grounded Text-to-Image Generation
Large-scale text-to-image diffusion models have made amazing advances.
Ranked #1 on
Text-to-Image Generation
on COCO
