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08/28/2023
Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation
Deep-learning models for 3D point cloud semantic segmentation exhibit li...
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08/18/2023
On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers
State-of-the-art rehearsal-free continual learning methods exploit the p...
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08/17/2023
The Unreasonable Effectiveness of Large Language-Vision Models for Source-free Video Domain Adaptation
Source-Free Video Unsupervised Domain Adaptation (SFVUDA) methods consis...
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07/31/2023
Interactive Neural Painting
In the last few years, Neural Painting (NP) techniques became capable of...
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07/18/2023
Object-aware Gaze Target Detection
Gaze target detection aims to predict the image location where the perso...
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07/04/2023
Unsupervised Video Anomaly Detection with Diffusion Models Conditioned on Compact Motion Representations
This paper aims to address the unsupervised video anomaly detection (VAD...
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06/13/2023
Semi-supervised learning made simple with self-supervised clustering
Self-supervised learning models have been shown to learn rich visual rep...
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05/09/2023
Rotation Synchronization via Deep Matrix Factorization
In this paper we address the rotation synchronization problem, where the...
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04/23/2023
Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation
The ability to deploy robots that can operate safely in diverse environm...
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04/12/2023
Exploring Diffusion Models for Unsupervised Video Anomaly Detection
This paper investigates the performance of diffusion models for video an...
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04/03/2023
AutoLabel: CLIP-based framework for Open-set Video Domain Adaptation
Open-set Unsupervised Video Domain Adaptation (OUVDA) deals with the tas...
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03/28/2023
Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery
Discovering novel concepts from unlabelled data and in a continuous mann...
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03/27/2023
Quantum Multi-Model Fitting
Geometric model fitting is a challenging but fundamental computer vision...
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03/23/2023
Plotting Behind the Scenes: Towards Learnable Game Engines
Game engines are powerful tools in computer graphics. Their power comes ...
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03/21/2023
Novel Class Discovery for 3D Point Cloud Semantic Segmentation
Novel class discovery (NCD) for semantic segmentation is the task of lea...
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02/18/2023
StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization
Large-scale foundation models (e.g., CLIP) have shown promising zero-sho...
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01/09/2023
Simplifying Open-Set Video Domain Adaptation with Contrastive Learning
In an effort to reduce annotation costs in action recognition, unsupervi...
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12/09/2022
A soft nearest-neighbor framework for continual semi-supervised learning
Despite significant advances, the performance of state-of-the-art contin...
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10/17/2022
Overlap-guided Gaussian Mixture Models for Point Cloud Registration
Probabilistic 3D point cloud registration methods have shown competitive...
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10/06/2022
Data Augmentation-free Unsupervised Learning for 3D Point Cloud Understanding
Unsupervised learning on 3D point clouds has undergone a rapid evolution...
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10/04/2022
Cooperative Self-Training for Multi-Target Adaptive Semantic Segmentation
In this work we address multi-target domain adaptation (MTDA) in semanti...
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08/23/2022
Multimodal Across Domains Gaze Target Detection
This paper addresses the gaze target detection problem in single images ...
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08/16/2022
Uncertainty-guided Source-free Domain Adaptation
Source-free domain adaptation (SFDA) aims to adapt a classifier to an un...
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07/23/2022
Multimodal Emotion Recognition with Modality-Pairwise Unsupervised Contrastive Loss
Emotion recognition is involved in several real-world applications. With...
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07/20/2022
CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation
3D LiDAR semantic segmentation is fundamental for autonomous driving. Se...
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07/20/2022
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation
3D point cloud semantic segmentation is fundamental for autonomous drivi...
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07/18/2022
Class-incremental Novel Class Discovery
We study the new task of class-incremental Novel Class Discovery (class-...
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03/26/2022
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
A fundamental and challenging problem in deep learning is catastrophic f...
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03/24/2022
Quantum Motion Segmentation
Motion segmentation is a challenging problem that seeks to identify inde...
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03/03/2022
Playable Environments: Video Manipulation in Space and Time
We present Playable Environments - a new representation for interactive ...
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02/07/2022
3D Object Detection from Images for Autonomous Driving: A Survey
3D object detection from images, one of the fundamental and challenging ...
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02/01/2022
Continual Attentive Fusion for Incremental Learning in Semantic Segmentation
Over the past years, semantic segmentation, as many other tasks in compu...
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01/31/2022
Modeling the Background for Incremental and Weakly-Supervised Semantic Segmentation
Deep neural networks have enabled major progresses in semantic segmentat...
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12/08/2021
Self-Supervised Models are Continual Learners
Self-supervised models have been shown to produce comparable or better v...
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11/19/2021
Global and Local Alignment Networks for Unpaired Image-to-Image Translation
The goal of unpaired image-to-image translation is to produce an output ...
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11/19/2021
Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation
In autonomous driving, learning a segmentation model that can adapt to v...
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08/19/2021
Click to Move: Controlling Video Generation with Sparse Motion
This paper introduces Click to Move (C2M), a novel framework for video g...
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08/19/2021
A Unified Objective for Novel Class Discovery
In this paper, we study the problem of Novel Class Discovery (NCD). NCD ...
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08/03/2021
Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning
This paper presents solo-learn, a library of self-supervised methods for...
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06/20/2021
Neighborhood Contrastive Learning for Novel Class Discovery
In this paper, we address Novel Class Discovery (NCD), the task of unvei...
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05/28/2021
Transformer-Based Source-Free Domain Adaptation
In this paper, we study the task of source-free domain adaptation (SFDA)...
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04/01/2021
Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation
In this paper we address multi-target domain adaptation (MTDA), where gi...
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03/25/2021
Boosting Binary Masks for Multi-Domain Learning through Affine Transformations
In this work, we present a new, algorithm for multi-domain learning. Giv...
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03/25/2021
Inferring Latent Domains for Unsupervised Deep Domain Adaptation
Unsupervised Domain Adaptation (UDA) refers to the problem of learning a...
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03/22/2021
Transformers Solve the Limited Receptive Field for Monocular Depth Prediction
While convolutional neural networks have shown a tremendous impact on va...
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03/05/2021
Variational Structured Attention Networks for Deep Visual Representation Learning
Convolutional neural networks have enabled major progress in addressing ...
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01/28/2021
Playable Video Generation
This paper introduces the unsupervised learning problem of playable vide...
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01/11/2021
Multi-Domain Image-to-Image Translation with Adaptive Inference Graph
In this work, we address the problem of multi-domain image-to-image tran...
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01/08/2021
Probabilistic Graph Attention Network with Conditional Kernels for Pixel-Wise Prediction
Multi-scale representations deeply learned via convolutional neural netw...
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12/10/2020