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Unbiased Teacher for Semi-Supervised Object Detection
Semi-supervised learning, i.e., training networks with both labeled and ...
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FBWave: Efficient and Scalable Neural Vocoders for Streaming Text-To-Speech on the Edge
Nowadays more and more applications can benefit from edge-based text-to-...
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One Shot 3D Photography
3D photography is a new medium that allows viewers to more fully experie...
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Geometric Correspondence Fields: Learned Differentiable Rendering for 3D Pose Refinement in the Wild
We present a novel 3D pose refinement approach based on differentiable r...
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Visual Transformers: Token-based Image Representation and Processing for Computer Vision
Computer vision has achieved great success using standardized image repr...
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FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function
Neural Architecture Search (NAS) yields state-of-the-art neural networks...
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FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions
Differentiable Neural Architecture Search (DNAS) has demonstrated great ...
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Deep Space-Time Video Upsampling Networks
Video super-resolution (VSR) and frame interpolation (FI) are traditiona...
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SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation
LiDAR point-cloud segmentation is an important problem for many applicat...
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Learning the Loss Functions in a Discriminative Space for Video Restoration
With more advanced deep network architectures and learning schemes such ...
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Efficient Segmentation: Learning Downsampling Near Semantic Boundaries
Many automated processes such as auto-piloting rely on a good semantic s...
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Learning to Generate Grounded Image Captions without Localization Supervision
When generating a sentence description for an image, it frequently remai...
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Precision Highway for Ultra Low-Precision Quantization
Neural network quantization has an inherent problem called accumulated q...
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ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation
This paper proposes an efficient neural network (NN) architecture design...
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FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search
Designing accurate and efficient ConvNets for mobile devices is challeng...
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Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search
Recent work in network quantization has substantially reduced the time a...
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Value-aware Quantization for Training and Inference of Neural Networks
We propose a novel value-aware quantization which applies aggressively r...
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DSD: Dense-Sparse-Dense Training for Deep Neural Networks
Modern deep neural networks have a large number of parameters, making th...
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