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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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11/18/2022
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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11/12/2022
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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12/27/2021
A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision
Using natural language as a supervision for training visual recognition ...
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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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11/25/2021
Cross-Domain Object Detection via Adaptive Self-Training
We tackle the problem of domain adaptation in object detection, where th...
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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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10/25/2021
Differentiable NAS Framework and Application to Ads CTR Prediction
Neural architecture search (NAS) methods aim to automatically find the o...
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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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11/22/2020
FP-NAS: Fast Probabilistic Neural Architecture Search
Differential Neural Architecture Search (NAS) requires all layer choices...
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09/01/2020
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation
Large-scale labeled training datasets have enabled deep neural networks ...
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06/12/2020
CoDeNet: Algorithm-hardware Co-design for Deformable Convolution
Deploying deep learning models on embedded systems for computer vision t...
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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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04/03/2020
SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation
LiDAR point-cloud segmentation is an important problem for many applicat...
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02/19/2020
Algorithm-hardware Co-design for Deformable Convolution
FPGAs provide a flexible and efficient platform to accelerate rapidly-ch...
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01/16/2020
SqueezeWave: Extremely Lightweight Vocoders for On-device Speech Synthesis
Automatic speech synthesis is a challenging task that is becoming increa...
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11/26/2019
Domain-Aware Dynamic Networks
Deep neural networks with more parameters and FLOPs have higher capacity...
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08/20/2019
Efficient Deep Neural Networks
The success of deep neural networks (DNNs) is attributable to three fact...
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04/19/2019
LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Tracking
LiDAR (Light Detection And Ranging) is an essential and widely adopted s...
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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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11/21/2018
Synetgy: Algorithm-hardware Co-design for ConvNet Accelerators on Embedded FPGAs
Using FPGAs to accelerate ConvNets has attracted significant attention i...
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09/22/2018
SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud
Earlier work demonstrates the promise of deep-learning-based approaches ...
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04/20/2018
Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications
Deep Learning is arguably the most rapidly evolving research area in rec...
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03/31/2018
A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving
3D LiDAR scanners are playing an increasingly important role in autonomo...
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03/24/2018
Unsupervised Domain Adaptation: from Simulation Engine to the RealWorld
Large-scale labeled training datasets have enabled deep neural networks ...
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03/23/2018
SqueezeNext: Hardware-Aware Neural Network Design
One of the main barriers for deploying neural networks on embedded syste...
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11/22/2017
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
Neural networks rely on convolutions to aggregate spatial information. H...
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10/19/2017
SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud
In this paper, we address semantic segmentation of road-objects from 3D ...
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12/04/2016
SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving
Object detection is a crucial task for autonomous driving. In addition t...
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06/05/2016