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02/26/2023
Learning cross space mapping via DNN using large scale click-through logs
The gap between low-level visual signals and high-level semantics has be...
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07/10/2022
SFNet: Faster, Accurate, and Domain Agnostic Semantic Segmentation via Semantic Flow
In this paper, we focus on exploring effective methods for faster, accur...
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07/28/2021
Improving Video Instance Segmentation via Temporal Pyramid Routing
Video Instance Segmentation (VIS) is a new and inherently multi-task pro...
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07/28/2021
Global Aggregation then Local Distribution for Scene Parsing
Modelling long-range contextual relationships is critical for pixel-wise...
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05/25/2021
BoundarySqueeze: Image Segmentation as Boundary Squeezing
We propose a novel method for fine-grained high-quality image segmentati...
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11/06/2020
Towards Efficient Scene Understanding via Squeeze Reasoning
Graph-based convolutional model such as non-local block has shown to be ...
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07/21/2020
Feature-metric Loss for Self-supervised Learning of Depth and Egomotion
Photometric loss is widely used for self-supervised depth and egomotion ...
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02/24/2020
Semantic Flow for Fast and Accurate Scene Parsing
In this paper, we focus on effective methods for fast and accurate scene...
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09/16/2019
Global Aggregation then Local Distribution in Fully Convolutional Networks
It has been widely proven that modelling long-range dependencies in full...
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09/13/2019
Dual Graph Convolutional Network for Semantic Segmentation
Exploiting long-range contextual information is key for pixel-wise predi...
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09/09/2019
Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching
State-of-the-art deep learning based stereo matching approaches treat di...
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04/03/2019
GFF: Gated Fully Fusion for Semantic Segmentation
Semantic segmentation generates comprehensive understanding of scenes at...
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08/28/2017
Automatic Dataset Augmentation
Large scale image dataset and deep convolutional neural network (DCNN) a...
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05/29/2017
Feature Incay for Representation Regularization
Softmax loss is widely used in deep neural networks for multi-class clas...
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11/17/2016
Hard-Aware Deeply Cascaded Embedding
Riding on the waves of deep neural networks, deep metric learning has al...
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12/20/2014
Visualizing and Comparing Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have achieved comparable error rate...
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11/24/2014
The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification
Fine-grained classification is challenging because categories can only b...
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11/24/2014
Scale-Invariant Convolutional Neural Networks
Even though convolutional neural networks (CNN) has achieved near-human ...
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12/17/2013