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06/26/2023
Hierarchical Matching and Reasoning for Multi-Query Image Retrieval
As a promising field, Multi-Query Image Retrieval (MQIR) aims at searchi...
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06/06/2023
DFormer: Diffusion-guided Transformer for Universal Image Segmentation
This paper introduces an approach, named DFormer, for universal image se...
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06/05/2023
Image Reconstruction for Accelerated MR Scan with Faster Fourier Convolutional Neural Networks
Partial scan is a common approach to accelerate Magnetic Resonance Imagi...
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04/24/2023
Transformer-based stereo-aware 3D object detection from binocular images
Vision Transformers have shown promising progress in various object dete...
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03/21/2023
LEAPS: End-to-End One-Step Person Search With Learnable Proposals
We propose an end-to-end one-step person search approach with learnable ...
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02/09/2023
Deep Intra-Image Contrastive Learning for Weakly Supervised One-Step Person Search
Weakly supervised person search aims to perform joint pedestrian detecti...
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01/17/2023
USER: Unified Semantic Enhancement with Momentum Contrast for Image-Text Retrieval
As a fundamental and challenging task in bridging language and vision do...
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08/11/2022
Memorizing Complementation Network for Few-Shot Class-Incremental Learning
Few-shot Class-Incremental Learning (FSCIL) aims at learning new concept...
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08/10/2022
Multi-scale Feature Aggregation for Crowd Counting
Convolutional Neural Network (CNN) based crowd counting methods have ach...
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04/07/2022
PSTR: End-to-End One-Step Person Search With Transformers
We propose a novel one-step transformer-based person search framework, P...
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03/11/2022
Active Phase-Encode Selection for Slice-Specific Fast MR Scanning Using a Transformer-Based Deep Reinforcement Learning Framework
Purpose: Long scan time in phase encoding for forming complete K-space m...
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03/11/2022
Dual-Domain Reconstruction Networks with V-Net and K-Net for fast MRI
Purpose: To introduce a dual-domain reconstruction network with V-Net an...
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11/28/2021
EGFN: Efficient Geometry Feature Network for Fast Stereo 3D Object Detection
Fast stereo based 3D object detectors have made great progress in the se...
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09/03/2021
Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decomposition
The domain shift between the source and target domain is the main challe...
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09/03/2021
Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning
Semantic information provides intra-class consistency and inter-class di...
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06/18/2021
Shape Prior Non-Uniform Sampling Guided Real-time Stereo 3D Object Detection
Pseudo-LiDAR based 3D object detectors have gained popularity due to the...
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11/18/2020
TJU-DHD: A Diverse High-Resolution Dataset for Object Detection
Vehicles, pedestrians, and riders are the most important and interesting...
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10/01/2020
From Handcrafted to Deep Features for Pedestrian Detection: A Survey
Pedestrian detection is an important but challenging problem in computer...
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07/29/2020
SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation
Single-stage instance segmentation approaches have recently gained popul...
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07/17/2020
Consensus-Aware Visual-Semantic Embedding for Image-Text Matching
Image-text matching plays a central role in bridging vision and language...
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03/10/2020
Hierarchical Human Parsing with Typed Part-Relation Reasoning
Human parsing is for pixel-wise human semantic understanding. As human b...
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01/25/2020
PSC-Net: Learning Part Spatial Co-occurence for Occluded Pedestrian Detection
Detecting pedestrians, especially under heavy occlusions, is a challengi...
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01/19/2020
Learning Compositional Neural Information Fusion for Human Parsing
This work proposes to combine neural networks with the compositional hie...
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01/18/2020
NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection
Due to the advantages of real-time detection and improved performance, s...
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10/17/2019
Deep Contextual Attention for Human-Object Interaction Detection
Human-object interaction detection is an important and relatively new cl...
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10/14/2019
Mask-Guided Attention Network for Occluded Pedestrian Detection
Pedestrian detection relying on deep convolution neural networks has mad...
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08/26/2019
A Semantics-Guided Class Imbalance Learning Model for Zero-Shot Classification
Zero-Shot Classification (ZSC) equips the learned model with the ability...
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07/25/2019
ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation
Segmentation is a fundamental task in medical image analysis. However, m...
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04/20/2019
Saliency-Guided Attention Network for Image-Sentence Matching
This paper studies the task of matching image and sentence, where learni...
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11/20/2018
Bi-Adversarial Auto-Encoder for Zero-Shot Learning
Existing generative Zero-Shot Learning (ZSL) methods only consider the u...
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09/25/2018
Triply Supervised Decoder Networks for Joint Detection and Segmentation
Joint object detection and semantic segmentation can be applied to many ...
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05/21/2018
Stacked Semantic-Guided Attention Model for Fine-Grained Zero-Shot Learning
Zero-Shot Learning (ZSL) is achieved via aligning the semantic relations...
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04/03/2018
Exploring Multi-Branch and High-Level Semantic Networks for Improving Pedestrian Detection
To better detect pedestrians of various scales, deep multi-scale methods...
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03/21/2018
A Cascaded Convolutional Neural Network for Single Image Dehazing
Images captured under outdoor scenes usually suffer from low contrast an...
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02/06/2018
Attribute-Guided Network for Cross-Modal Zero-Shot Hashing
Zero-Shot Hashing aims at learning a hashing model that is trained only ...
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09/09/2017
Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction
Explicitly or implicitly, most of dimensionality reduction methods need ...
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07/13/2017
Query-Aware Sparse Coding for Multi-Video Summarization
Given the explosive growth of online videos, it is becoming increasingly...
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05/22/2017
Semantic Softmax Loss for Zero-Shot Learning
A typical pipeline for Zero-Shot Learning (ZSL) is to integrate the visu...
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03/27/2017
Transductive Zero-Shot Learning with Adaptive Structural Embedding
Zero-shot learning (ZSL) endows the computer vision system with the infe...
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06/30/2016
Zero-Shot Learning with Multi-Battery Factor Analysis
Zero-shot learning (ZSL) extends the conventional image classification t...
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03/22/2016
Convolution in Convolution for Network in Network
Network in Netwrok (NiN) is an effective instance and an important exten...
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03/01/2016
Cascaded Subpatch Networks for Effective CNNs
Conventional Convolutional Neural Networks (CNNs) use either a linear or...
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03/01/2016
