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10/04/2022
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models
This paper presents MOAT, a family of neural networks that build on top ...
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07/08/2022
k-means Mask Transformer
The rise of transformers in vision tasks not only advances network backb...
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06/17/2022
CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation
We propose Clustering Mask Transformer (CMT-DeepLab), a transformer-base...
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06/15/2022
Waymo Open Dataset: Panoramic Video Panoptic Segmentation
Panoptic image segmentation is the computer vision task of finding group...
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06/17/2021
DeepLab2: A TensorFlow Library for Deep Labeling
DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a ...
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05/07/2021
BasisNet: Two-stage Model Synthesis for Efficient Inference
In this work, we present BasisNet which combines recent advancements in ...
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04/26/2021
Joint Representation Learning and Novel Category Discovery on Single- and Multi-modal Data
This paper studies the problem of novel category discovery on single- an...
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02/23/2021
STEP: Segmenting and Tracking Every Pixel
In this paper, we tackle video panoptic segmentation, a task that requir...
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12/09/2020
ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation
In this paper, we present ViP-DeepLab, a unified model attempting to tac...
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12/01/2020
MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers
We present MaX-DeepLab, the first end-to-end model for panoptic segmenta...
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11/23/2020
Ranking Neural Checkpoints
This paper is concerned with ranking many pre-trained deep neural networ...
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10/15/2020
Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze
Mutual gaze detection, i.e., predicting whether or not two people are lo...
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03/17/2020
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation
Convolution exploits locality for efficiency at a cost of missing long r...
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11/22/2019
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
In this work, we introduce Panoptic-DeepLab, a simple, strong, and fast ...
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11/20/2019
Search to Distill: Pearls are Everywhere but not the Eyes
Standard Knowledge Distillation (KD) approaches distill the knowledge of...
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10/10/2019
Panoptic-DeepLab
We present Panoptic-DeepLab, a bottom-up and single-shot approach for pa...
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08/26/2019
SPGNet: Semantic Prediction Guidance for Scene Parsing
Multi-scale context module and single-stage encoder-decoder structure ar...
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05/06/2019
Searching for MobileNetV3
We present the next generation of MobileNets based on a combination of c...
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02/13/2019
DeeperLab: Single-Shot Image Parser
We present a single-shot, bottom-up approach for whole image parsing. Wh...
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09/11/2018
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
The design of neural network architectures is an important component for...
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02/07/2018
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Spatial pyramid pooling module or encode-decoder structure are used in d...
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12/07/2016
Spatially Adaptive Computation Time for Residual Networks
This paper proposes a deep learning architecture based on Residual Netwo...
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08/27/2016
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection
The goal of this paper is to perform 3D object detection in the context ...
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12/09/2015
MovieQA: Understanding Stories in Movies through Question-Answering
We introduce the MovieQA dataset which aims to evaluate automatic story ...
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06/22/2015
Skip-Thought Vectors
We describe an approach for unsupervised learning of a generic, distribu...
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06/22/2015
Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books
Books are a rich source of both fine-grained information, how a characte...
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02/15/2015
