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06/05/2023
Bridging the Domain Gap between Synthetic and Real-World Data for Autonomous Driving
Modern autonomous systems require extensive testing to ensure reliabilit...
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06/02/2023
Temporal-controlled Frame Swap for Generating High-Fidelity Stereo Driving Data for Autonomy Analysis
This paper presents a novel approach, TeFS (Temporal-controlled Frame Sw...
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05/29/2023
SPAC-Net: Synthetic Pose-aware Animal ControlNet for Enhanced Pose Estimation
Animal pose estimation has become a crucial area of research, but the sc...
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02/01/2023
TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation
Model parallelism has become necessary to train large neural networks. H...
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08/30/2022
Prior-Aware Synthetic Data to the Rescue: Animal Pose Estimation with Very Limited Real Data
Accurately annotated image datasets are essential components for studyin...
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10/08/2021
M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
Recent expeditious developments in deep learning algorithms, distributed...
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05/31/2021
Exploring Sparse Expert Models and Beyond
Mixture-of-Experts (MoE) models can achieve promising results with outra...
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03/01/2021
M6: A Chinese Multimodal Pretrainer
In this work, we construct the largest dataset for multimodal pretrainin...
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11/18/2020