research
∙
08/29/2023
Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation
Federated learning (FL) emerges as a decentralized learning framework wh...
share
research
∙
07/19/2023
FedBug: A Bottom-Up Gradual Unfreezing Framework for Federated Learning
Federated Learning (FL) offers a collaborative training framework, allow...
research
∙
05/27/2023
Modality-Independent Teachers Meet Weakly-Supervised Audio-Visual Event Parser
Audio-visual learning has been a major pillar of multi-modal machine lea...
research
∙
02/19/2023
TAX: Tendency-and-Assignment Explainer for Semantic Segmentation with Multi-Annotators
To understand how deep neural networks perform classification prediction...
research
∙
11/26/2022
Target-Free Text-guided Image Manipulation
We tackle the problem of target-free text-guided image manipulation, whi...
research
∙
09/25/2022
Paraphrasing Is All You Need for Novel Object Captioning
Novel object captioning (NOC) aims to describe images containing objects...
research
∙
08/30/2022
Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond
While self-supervised learning has been shown to benefit a number of vis...
research
∙
08/29/2022
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Diffusion models (DMs) have shown great potential for high-quality image...
research
∙
08/16/2022
Learning Facial Liveness Representation for Domain Generalized Face Anti-spoofing
Face anti-spoofing (FAS) aims at distinguishing face spoof attacks from ...
research
∙
05/05/2022
Scene Graph Expansion for Semantics-Guided Image Outpainting
In this paper, we address the task of semantics-guided image outpainting...
research
∙
04/28/2022
NeurMiPs: Neural Mixture of Planar Experts for View Synthesis
We present Neural Mixtures of Planar Experts (NeurMiPs), a novel planar-...
research
∙
03/23/2022
Domain-Generalized Textured Surface Anomaly Detection
Anomaly detection aims to identify abnormal data that deviates from the ...
research
∙
12/27/2021
Few-Shot Classification in Unseen Domains by Episodic Meta-Learning Across Visual Domains
Few-shot classification aims to carry out classification given only few ...
research
∙
12/27/2021
Meta-Learned Feature Critics for Domain Generalized Semantic Segmentation
How to handle domain shifts when recognizing or segmenting visual data a...
research
∙
11/02/2021
A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation
Few-shot semantic segmentation addresses the learning task in which only...
research
∙
05/03/2021
Exploiting Audio-Visual Consistency with Partial Supervision for Spatial Audio Generation
Human perceives rich auditory experience with distinct sound heard by ea...
research
∙
02/26/2021
Dual-MTGAN: Stochastic and Deterministic Motion Transfer for Image-to-Video Synthesis
Generating videos with content and motion variations is a challenging ta...
research
∙
11/02/2020
Deep Representation Decomposition for Feature Disentanglement
Representation disentanglement aims at learning interpretable features, ...
research
∙
10/21/2020
Semantics-Guided Representation Learning with Applications to Visual Synthesis
Learning interpretable and interpolatable latent representations has bee...
research
∙
10/19/2020
Domain Generalized Person Re-Identification via Cross-Domain Episodic Learning
Aiming at recognizing images of the same person across distinct camera v...
research
∙
10/02/2020
Semantics-Guided Clustering with Deep Progressive Learning for Semi-Supervised Person Re-identification
Person re-identification (re-ID) requires one to match images of the sam...
research
∙
08/25/2020
Learning to Learn in a Semi-Supervised Fashion
To address semi-supervised learning from both labeled and unlabeled data...
research
∙
07/17/2020
Wavelet Channel Attention Module with a Fusion Network for Single Image Deraining
Single image deraining is a crucial problem because rain severely degene...
research
∙
06/02/2020
Transforming Multi-Concept Attention into Video Summarization
Video summarization is among challenging tasks in computer vision, which...
research
∙
06/02/2020
Transfoming Multi-Concept Attention into Video Summarization
Video summarization is among challenging tasks in computer vision, which...
research
∙
02/19/2020
Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond
Person re-identification (re-ID) aims at matching images of the same per...
research
∙
09/20/2019
Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation
Person re-identification (re-ID) aims at recognizing the same person fro...
research
∙
08/16/2019
Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification
Person re-identification (re-ID) aims at matching images of the same ide...
research
∙
08/05/2019
Spatially and Temporally Efficient Non-local Attention Network for Video-based Person Re-Identification
Video-based person re-identification (Re-ID) aims at matching video sequ...
research
∙
07/25/2019
Learning Resolution-Invariant Deep Representations for Person Re-Identification
Person re-identification (re-ID) solves the task of matching images acro...
research
∙
04/08/2019
A Closer Look at Few-shot Classification
Few-shot classification aims to learn a classifier to recognize unseen c...
research
∙
02/20/2019
Dual-modality seq2seq network for audio-visual event localization
Audio-visual event localization requires one to identify theevent which ...
research
∙
11/29/2018
3D Shape Reconstruction from a Single 2D Image via 2D-3D Self-Consistency
Aiming at inferring 3D shapes from 2D images, 3D shape reconstruction ha...
research
∙
09/05/2018
A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation
We present a novel and unified deep learning framework which is capable ...
research
∙
05/05/2018
Deep Reinforcement Learning for Playing 2.5D Fighting Games
Deep reinforcement learning has shown its success in game playing. Howev...
research
∙
04/25/2018
Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification
Person re-identification (Re-ID) aims at recognizing the same person fro...
research
∙
11/24/2017
For Your Eyes Only: Learning to Summarize First-Person Videos
With the increasing amount of video data, it is desirable to highlight o...
research
∙
11/17/2017
Multi-Label Zero-Shot Learning with Structured Knowledge Graphs
In this paper, we propose a novel deep learning architecture for multi-l...
research
∙
07/18/2017
Order-Free RNN with Visual Attention for Multi-Label Classification
In this paper, we propose the joint learning attention and recurrent neu...
research
∙
05/03/2017
Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation
While representation learning aims to derive interpretable features for ...
research
∙
04/27/2017
