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07/22/2023
Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes
Object detection via inaccurate bounding boxes supervision has boosted a...
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02/28/2023
Generic-to-Specific Distillation of Masked Autoencoders
Large vision Transformers (ViTs) driven by self-supervised pre-training ...
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12/16/2022
DQnet: Cross-Model Detail Querying for Camouflaged Object Detection
Camouflaged objects are seamlessly blended in with their surroundings, w...
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11/23/2022
Integrally Pre-Trained Transformer Pyramid Networks
In this paper, we present an integral pre-training framework based on ma...
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03/27/2022
Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers
The past year has witnessed a rapid development of masked image modeling...
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12/31/2021
P2P-Loc: Point to Point Tiny Person Localization
Bounding-box annotation form has been the most frequently used method fo...
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12/05/2021
Exploring Complicated Search Spaces with Interleaving-Free Sampling
The existing neural architecture search algorithms are mostly working on...
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11/29/2021
Feature-Gate Coupling for Dynamic Network Pruning
Gating modules have been widely explored in dynamic network pruning to r...
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11/25/2021
Semantic-Aware Generation for Self-Supervised Visual Representation Learning
In this paper, we propose a self-supervised visual representation learni...
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10/06/2021
Long-tailed Distribution Adaptation
Recognizing images with long-tailed distributions remains a challenging ...
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09/17/2021
GraFormer: Graph Convolution Transformer for 3D Pose Estimation
Exploiting relations among 2D joints plays a crucial role yet remains se...
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06/01/2021
Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation
Encouraging progress in few-shot semantic segmentation has been made by ...
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05/09/2021
Conformer: Local Features Coupling Global Representations for Visual Recognition
Within Convolutional Neural Network (CNN), the convolution operations ar...
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11/08/2020
Adaptive Linear Span Network for Object Skeleton Detection
Conventional networks for object skeleton detection are usually hand-cra...
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08/10/2020
Prototype Mixture Models for Few-shot Semantic Segmentation
Few-shot segmentation is challenging because objects within the support ...
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07/07/2020
Discretization-Aware Architecture Search
The search cost of neural architecture search (NAS) has been largely red...
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03/15/2020
Vision-Dialog Navigation by Exploring Cross-modal Memory
Vision-dialog navigation posed as a new holy-grail task in vision-langua...
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04/11/2019
C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection
Weakly supervised object detection (WSOD) is a challenging task when pro...
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02/16/2019
Min-Entropy Latent Model for Weakly Supervised Object Detection
Weakly supervised object detection is a challenging task when provided w...
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01/02/2019
SIXray : A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images
In this paper, we present a large-scale dataset and establish a baseline...
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12/03/2018
Domain Alignment with Triplets
Deep domain adaptation methods can reduce the distribution discrepancy b...
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11/26/2018
Similarity-preserving Image-image Domain Adaptation for Person Re-identification
This article studies the domain adaptation problem in person re-identifi...
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07/17/2018
SRN: Side-output Residual Network for Object Reflection Symmetry Detection and Beyond
In this paper, we establish a baseline for object reflection symmetry de...
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04/03/2018
Weakly Supervised Instance Segmentation using Class Peak Response
Weakly supervised instance segmentation with image-level labels, instead...
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11/19/2017
Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification
Person re-identification (re-ID) models trained on one domain often fail...
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09/06/2017
Soft Proposal Networks for Weakly Supervised Object Localization
Weakly supervised object localization remains challenging, where only im...
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03/07/2017
SRN: Side-output Residual Network for Object Symmetry Detection in the Wild
In this paper, we establish a baseline for object symmetry detection in ...
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01/07/2017
Oriented Response Networks
Deep Convolution Neural Networks (DCNNs) are capable of learning unprece...
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09/19/2016
