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08/23/2023
DR-Tune: Improving Fine-tuning of Pretrained Visual Models by Distribution Regularization with Semantic Calibration
The visual models pretrained on large-scale benchmarks encode general kn...
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08/04/2023
CTP-Net: Character Texture Perception Network for Document Image Forgery Localization
Due to the progression of information technology in recent years, docume...
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03/25/2023
Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images
Object detection on drone images with low-latency is an important but ch...
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03/22/2023
OcTr: Octree-based Transformer for 3D Object Detection
A key challenge for LiDAR-based 3D object detection is to capture suffic...
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01/04/2023
Emergent collective intelligence from massive-agent cooperation and competition
Inspired by organisms evolving through cooperation and competition betwe...
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10/24/2022
Multi-Agent Path Finding via Tree LSTM
In recent years, Multi-Agent Path Finding (MAPF) has attracted attention...
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07/11/2022
SHREC'22 Track: Sketch-Based 3D Shape Retrieval in the Wild
Sketch-based 3D shape retrieval (SBSR) is an important yet challenging t...
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04/17/2022
Entropy-based Active Learning for Object Detection with Progressive Diversity Constraint
Active learning is a promising alternative to alleviate the issue of hig...
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04/17/2022
Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection
Domain adaptive object detection (DAOD) is a promising way to alleviate ...
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04/01/2022
CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detection
In autonomous driving, LiDAR point-clouds and RGB images are two major d...
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12/20/2021
UFPMP-Det: Toward Accurate and Efficient Object Detection on Drone Imagery
This paper proposes a novel approach to object detection on drone imager...
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09/13/2021
Effectiveness of Pre-training for Few-shot Intent Classification
This paper investigates the effectiveness of pre-training for few-shot i...
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08/24/2021
Adaptation-Agnostic Meta-Training
Many meta-learning algorithms can be formulated into an interleaved proc...
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08/23/2021
PR-GCN: A Deep Graph Convolutional Network with Point Refinement for 6D Pose Estimation
RGB-D based 6D pose estimation has recently achieved remarkable progress...
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04/30/2021
Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification
Video-based person re-identification (re-ID) is an important research to...
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04/29/2021
Learning Multi-Attention Context Graph for Group-Based Re-Identification
Learning to re-identify or retrieve a group of people across non-overlap...
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10/09/2020
Deep Adversarial Domain Adaptation Based on Multi-layer Joint Kernelized Distance
Domain adaptation refers to the learning scenario that a model learned f...
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07/24/2020
Adaptive Energy Management for Real Driving Conditions via Transfer Reinforcement Learning
This article proposes a transfer reinforcement learning (RL) based adapt...
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07/16/2020
Transferred Energy Management Strategies for Hybrid Electric Vehicles Based on Driving Conditions Recognition
Energy management strategies (EMSs) are the most significant components ...
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02/27/2020
Auto-Encoding Twin-Bottleneck Hashing
Conventional unsupervised hashing methods usually take advantage of simi...
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12/26/2019
Variational Metric Scaling for Metric-Based Meta-Learning
Metric-based meta-learning has attracted a lot of attention due to its e...
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08/26/2019
Embarrassingly Simple Binary Representation Learning
Recent binary representation learning models usually require sophisticat...
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07/04/2018
Deep Cross-modality Adaptation via Semantics Preserving Adversarial Learning for Sketch-based 3D Shape Retrieval
Due to the large cross-modality discrepancy between 2D sketches and 3D s...
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02/20/2018
Scale Optimization for Full-Image-CNN Vehicle Detection
Many state-of-the-art general object detection methods make use of share...
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12/06/2017