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07/27/2023
NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection
We present NeRF-Det, a novel method for indoor 3D detection with posed R...
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12/05/2022
INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors
We present a method that accelerates reconstruction of 3D scenes and obj...
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11/19/2022
A Practical Stereo Depth System for Smart Glasses
We present the design of a productionized end-to-end stereo depth sensin...
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11/18/2022
Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference
Vision Transformers (ViTs) have shown impressive performance but still r...
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11/16/2022
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse
Real-time multi-model multi-task (MMMT) workloads, a new form of deep le...
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11/12/2022
3D-Aware Encoding for Style-based Neural Radiance Fields
We tackle the task of NeRF inversion for style-based neural radiance fie...
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10/09/2022
Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP
Open-vocabulary semantic segmentation aims to segment an image into sema...
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08/29/2022
Open-Set Semi-Supervised Object Detection
Recent developments for Semi-Supervised Object Detection (SSOD) have sho...
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12/17/2021
Data Efficient Language-supervised Zero-shot Recognition with Optimal Transport Distillation
Traditional computer vision models are trained to predict a fixed set of...
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11/19/2021
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run
Neural Architecture Search (NAS) has been widely adopted to design accur...
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06/08/2021
Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets
3D point-clouds and 2D images are different visual representations of th...
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04/18/2021
Data-Efficient Language-Supervised Zero-Shot Learning with Self-Distillation
Traditional computer vision models are trained to predict a fixed set of...
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03/18/2021
You Only Group Once: Efficient Point-Cloud Processing with Token Representation and Relation Inference Module
3D point-cloud-based perception is a challenging but crucial computer vi...
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02/18/2021
Unbiased Teacher for Semi-Supervised Object Detection
Semi-supervised learning, i.e., training networks with both labeled and ...
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11/25/2020
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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08/27/2020
One Shot 3D Photography
3D photography is a new medium that allows viewers to more fully experie...
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07/17/2020
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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06/05/2020
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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06/03/2020
FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function
Neural Architecture Search (NAS) yields state-of-the-art neural networks...
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04/12/2020
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions
Differentiable Neural Architecture Search (DNAS) has demonstrated great ...
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04/06/2020
Deep Space-Time Video Upsampling Networks
Video super-resolution (VSR) and frame interpolation (FI) are traditiona...
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04/03/2020
SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation
LiDAR point-cloud segmentation is an important problem for many applicat...
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03/20/2020
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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07/16/2019
Efficient Segmentation: Learning Downsampling Near Semantic Boundaries
Many automated processes such as auto-piloting rely on a good semantic s...
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06/01/2019
Learning to Generate Grounded Image Captions without Localization Supervision
When generating a sentence description for an image, it frequently remai...
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12/24/2018
Precision Highway for Ultra Low-Precision Quantization
Neural network quantization has an inherent problem called accumulated q...
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12/21/2018
ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation
This paper proposes an efficient neural network (NN) architecture design...
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12/09/2018
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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11/30/2018
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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04/20/2018
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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07/15/2016