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09/14/2023
Deep Reinforcement Learning-based Scheduling in Edge and Fog Computing Environments
Edge/fog computing, as a distributed computing paradigm, satisfies the l...
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07/12/2023
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation
Generating unlabeled data has been recently shown to help address the fe...
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06/21/2023
Semi-Implicit Denoising Diffusion Models (SIDDMs)
Despite the proliferation of generative models, achieving fast sampling ...
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06/08/2023
An Efficient Transformer for Simultaneous Learning of BEV and Lane Representations in 3D Lane Detection
Accurately detecting lane lines in 3D space is crucial for autonomous dr...
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05/25/2023
CLIP3Dstyler: Language Guided 3D Arbitrary Neural Style Transfer
In this paper, we propose a novel language-guided 3D arbitrary neural st...
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04/20/2023
Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering
The rendering scheme in neural radiance field (NeRF) is effective in ren...
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03/31/2023
Knowledge Distillation for Feature Extraction in Underwater VSLAM
In recent years, learning-based feature detection and matching have outp...
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03/16/2023
Grab What You Need: Rethinking Complex Table Structure Recognition with Flexible Components Deliberation
Recently, Table Structure Recognition (TSR) task, aiming at identifying ...
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12/17/2022
TCFimt: Temporal Counterfactual Forecasting from Individual Multiple Treatment Perspective
Determining causal effects of temporal multi-intervention assists decisi...
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11/27/2022
3D Scene Creation and Rendering via Rough Meshes: A Lighting Transfer Avenue
This paper studies how to flexibly integrate reconstructed 3D models int...
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11/20/2022
Adaptive Edge-to-Edge Interaction Learning for Point Cloud Analysis
Recent years have witnessed the great success of deep learning on variou...
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10/04/2022
Strength-Adaptive Adversarial Training
Adversarial training (AT) is proved to reliably improve network's robust...
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09/21/2022
Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition
Skeleton-based action recognition receives increasing attention because ...
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09/07/2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso
Learning the underlying casual structure, represented by Directed Acycli...
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07/21/2022
MetaComp: Learning to Adapt for Online Depth Completion
Relying on deep supervised or self-supervised learning, previous methods...
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07/21/2022
Detecting Deepfake by Creating Spatio-Temporal Regularity Disruption
Despite encouraging progress in deepfake detection, generalization to un...
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07/07/2022
Harnessing Out-Of-Distribution Examples via Augmenting Content and Style
Machine learning models are vulnerable to Out-Of-Distribution (OOD) exam...
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07/07/2022
Style Interleaved Learning for Generalizable Person Re-identification
Domain generalization (DG) for person re-identification (ReID) is a chal...
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06/28/2022
Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation
An organ segmentation method that can generalize to unseen contrasts and...
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06/17/2022
Understanding Robust Overfitting of Adversarial Training and Beyond
Robust overfitting widely exists in adversarial training of deep network...
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06/09/2022
A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning
The generalization of model-based reinforcement learning (MBRL) methods ...
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05/30/2022
Robust Weight Perturbation for Adversarial Training
Overfitting widely exists in adversarial robust training of deep network...
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05/27/2022
Counterfactual Fairness with Partially Known Causal Graph
Fair machine learning aims to avoid treating individuals or sub-populati...
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05/27/2022
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models
State-of-the-art causal discovery methods usually assume that the observ...
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05/10/2022
On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis
The establishment of the link between causality and unsupervised domain ...
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04/18/2022
MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning
Binary pointwise labels (aka implicit feedback) are heavily leveraged by...
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01/30/2022
Do We Need to Penalize Variance of Losses for Learning with Label Noise?
Algorithms which minimize the averaged loss have been widely designed fo...
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12/07/2021
Federated Causal Discovery
Causal discovery aims to learn a causal graph from observational data. T...
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11/30/2021
CRIS: CLIP-Driven Referring Image Segmentation
Referring image segmentation aims to segment a referent via a natural li...
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10/04/2021
Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization
Domain generalization (DG) aims to learn from multiple source domains a ...
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09/24/2021
Unaligned Image-to-Image Translation by Learning to Reweight
Unsupervised image-to-image translation aims at learning the mapping fro...
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09/07/2021
Instance-dependent Label-noise Learning under a Structural Causal Model
Label noise will degenerate the performance of deep learning algorithms ...
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08/22/2021
Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification
Unsupervised Domain Adaptive (UDA) object re-identification (Re-ID) aims...
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08/19/2021
Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision
Deep learning has achieved remarkable success in medicalimage segmentati...
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07/19/2021
Exploring Set Similarity for Dense Self-supervised Representation Learning
By considering the spatial correspondence, dense self-supervised represe...
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07/10/2021
Kernel Mean Estimation by Marginalized Corrupted Distributions
Estimating the kernel mean in a reproducing kernel Hilbert space is a cr...
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06/11/2021
Adversarial Robustness through the Lens of Causality
The adversarial vulnerability of deep neural networks has attracted sign...
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06/01/2021
Instance Correction for Learning with Open-set Noisy Labels
The problem of open-set noisy labels denotes that part of training data ...
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06/01/2021
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels
In learning with noisy labels, the sample selection approach is very pop...
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03/17/2021
Learning with Group Noise
Machine learning in the context of noise is a challenging but practical ...
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10/23/2020
Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning
Image-based 3D shape retrieval (IBSR) aims to find the corresponding 3D ...
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10/22/2020
Deep Learning is Singular, and That's Good
In singular models, the optimal set of parameters forms an analytic set ...
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09/21/2020
3D-FUTURE: 3D Furniture shape with TextURE
The 3D CAD shapes in current 3D benchmarks are mostly collected from onl...
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08/25/2020
Adaptive Context-Aware Multi-Modal Network for Depth Completion
Depth completion aims to recover a dense depth map from the sparse depth...
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06/14/2020
Parts-dependent Label Noise: Towards Instance-dependent Label Noise
Learning with the instance-dependent label noise is challenging, because...
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06/14/2020
Class2Simi: A New Perspective on Learning with Label Noise
Label noise is ubiquitous in the era of big data. Deep learning algorith...
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06/14/2020
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning
The transition matrix, denoting the transition relationship from clean l...
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02/16/2020
Multi-Class Classification from Noisy-Similarity-Labeled Data
A similarity label indicates whether two instances belong to the same cl...
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02/10/2020
Towards Mixture Proportion Estimation without Irreducibility
Mixture proportion estimation (MPE) is a fundamental problem of practica...
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02/09/2020
