Martin Danelljan

research

∙ 08/23/2023

MolGrapher: Graph-based Visual Recognition of Chemical Structures

The automatic analysis of chemical literature has immense potential to a...

0 Lucas Morin, et al. ∙

research

∙ 08/06/2023

Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects

Camouflaged object detection (COD) is the challenging task of identifyin...

0 Chunming He, et al. ∙

research

∙ 07/20/2023

Cascade-DETR: Delving into High-Quality Universal Object Detection

Object localization in general environments is a fundamental part of vis...

0 Mingqiao Ye, et al. ∙

research

∙ 07/05/2023

Prompting Diffusion Representations for Cross-Domain Semantic Segmentation

While originally designed for image generation, diffusion models have re...

0 Rui Gong, et al. ∙

research

∙ 07/03/2023

Segment Anything Meets Point Tracking

The Segment Anything Model (SAM) has established itself as a powerful ze...

0 Frano Rajic, et al. ∙

research

∙ 04/30/2023

StyleGenes: Discrete and Efficient Latent Distributions for GANs

We propose a discrete latent distribution for Generative Adversarial Net...

0 Evangelos Ntavelis, et al. ∙

research

∙ 03/28/2023

Mask-Free Video Instance Segmentation

The recent advancement in Video Instance Segmentation (VIS) has largely ...

0 Lei Ke, et al. ∙

research

∙ 03/22/2023

NeRF-GAN Distillation for Memory-Efficient 3D-Aware Generation with Convolutions

Pose-conditioned convolutional generative models struggle with high-qual...

0 Mohamad Shahbazi, et al. ∙

research

∙ 02/07/2023

How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?

Many important computer vision applications are naturally formulated as ...

0 Fredrik K. Gustafsson, et al. ∙

research

∙ 10/10/2022

Fast Hierarchical Learning for Few-Shot Object Detection

Transfer learning based approaches have recently achieved promising resu...

13 Yihang She, et al. ∙

research

∙ 08/18/2022

ManiFlow: Implicitly Representing Manifolds with Normalizing Flows

Normalizing Flows (NFs) are flexible explicit generative models that hav...

9 Janis Postels, et al. ∙

research

∙ 08/14/2022

AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility

One of the key factors behind the recent success in visual tracking is t...

5 Mubashir Noman, et al. ∙

research

∙ 07/28/2022

Video Mask Transfiner for High-Quality Video Instance Segmentation

While Video Instance Segmentation (VIS) has seen rapid progress, current...

6 Lei Ke, et al. ∙

research

∙ 07/26/2022

Tracking Every Thing in the Wild

Current multi-category Multiple Object Tracking (MOT) metrics use class ...

3 Siyuan Li, et al. ∙

research

∙ 04/05/2022

Arbitrary-Scale Image Synthesis

Positional encodings have enabled recent works to train a single adversa...

0 Evangelos Ntavelis, et al. ∙

research

∙ 03/21/2022

Transforming Model Prediction for Tracking

Optimization based tracking methods have been widely successful by integ...

8 Christoph Mayer, et al. ∙

research

∙ 03/21/2022

Robust Visual Tracking by Segmentation

Estimating the target extent poses a fundamental challenge in visual obj...

7 Matthieu Paul, et al. ∙

research

∙ 03/20/2022

Transform your Smartphone into a DSLR Camera: Learning the ISP in the Wild

We propose a trainable Image Signal Processing (ISP) framework that prod...

25 Ardhendu Shekhar Tripathi, et al. ∙

research

∙ 03/08/2022

Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences

We propose Probabilistic Warp Consistency, a weakly-supervised learning ...

12 Prune Truong, et al. ∙

research

∙ 02/17/2022

Adiabatic Quantum Computing for Multi Object Tracking

Multi-Object Tracking (MOT) is most often approached in the tracking-by-...

16 Jan-Nico Zaech, et al. ∙

research

∙ 02/03/2022

Fast Online Video Super-Resolution with Deformable Attention Pyramid

Video super-resolution (VSR) has many applications that pose strict caus...

3 Dario Fuoli, et al. ∙

research

∙ 01/24/2022

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Free-form inpainting is the task of adding new content to an image in th...

5 Andreas Lugmayr, et al. ∙

research

∙ 01/17/2022

Collapse by Conditioning: Training Class-conditional GANs with Limited Data

Class-conditioning offers a direct means of controlling a Generative Adv...

9 Mohamad Shahbazi, et al. ∙

research

∙ 12/17/2021

Efficient Visual Tracking with Exemplar Transformers

The design of more complex and powerful neural network models has signif...

6 Philippe Blatter, et al. ∙

research

∙ 12/06/2021

Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook

Accurate and robust visual object tracking is one of the most challengin...

0 Sajid Javed, et al. ∙

research

∙ 11/26/2021

Mask Transfiner for High-Quality Instance Segmentation

Two-stage and query-based instance segmentation methods have achieved re...

0 Lei Ke, et al. ∙

research

∙ 11/05/2021

Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution

Super-resolution is an ill-posed problem, where a ground-truth high-reso...

11 Andreas Lugmayr, et al. ∙

research

∙ 10/22/2021

Learning Proposals for Practical Energy-Based Regression

Energy-based models (EBMs) have experienced a resurgence within machine ...

0 Fredrik K. Gustafsson, et al. ∙

research

∙ 10/07/2021

Dense Gaussian Processes for Few-Shot Segmentation

Few-shot segmentation is a challenging dense prediction task, which enta...

0 Joakim Johnander, et al. ∙

research

∙ 09/28/2021

PDC-Net+: Enhanced Probabilistic Dense Correspondence Network

Establishing robust and accurate correspondences between a pair of image...

14 Prune Truong, et al. ∙

research

∙ 09/10/2021

TADA: Taxonomy Adaptive Domain Adaptation

Traditional domain adaptation addresses the task of adapting a model to ...

0 Rui Gong, et al. ∙

research

∙ 08/18/2021

Deep Reparametrization of Multi-Frame Super-Resolution and Denoising

We propose a deep reparametrization of the maximum a posteriori formulat...

12 Goutam Bhat, et al. ∙

research

∙ 08/11/2021

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling

Normalizing flows have recently demonstrated promising results for low-l...

0 Jingyun Liang, et al. ∙

research

∙ 06/22/2021

Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation

Multiple object tracking and segmentation requires detecting, tracking, ...

0 Lei Ke, et al. ∙

research

∙ 06/07/2021

NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results

This paper reviews the NTIRE2021 challenge on burst super-resolution. Gi...

0 Goutam Bhat, et al. ∙

research

∙ 04/23/2021

Learnable Online Graph Representations for 3D Multi-Object Tracking

Tracking of objects in 3D is a fundamental task in computer vision that ...

0 Jan-Nico Zaech, et al. ∙

research

∙ 04/07/2021

Warp Consistency for Unsupervised Learning of Dense Correspondences

The key challenge in learning dense correspondences lies in the lack of ...

0 Prune Truong, et al. ∙

research

∙ 03/30/2021

Learning Target Candidate Association to Keep Track of What Not to Track

The presence of objects that are confusingly similar to the tracked targ...

0 Christoph Mayer, et al. ∙

research

∙ 03/30/2021

Deep Gaussian Processes for Few-Shot Segmentation

Few-shot segmentation is a challenging task, requiring the extraction of...

0 Joakim Johnander, et al. ∙

research

∙ 01/26/2021

Deep Burst Super-Resolution

While single-image super-resolution (SISR) has attracted substantial int...

27 Goutam Bhat, et al. ∙

research

∙ 01/14/2021

DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows

The difficulty of obtaining paired data remains a major bottleneck for l...

6 Valentin Wolf, et al. ∙

research

∙ 01/06/2021

Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videos

Segmenting objects in videos is a fundamental computer vision task. The ...

6 Bin Zhao, et al. ∙

research

∙ 01/05/2021

Local Memory Attention for Fast Video Semantic Segmentation

We propose a novel neural network module that transforms an existing sin...

4 Matthieu Paul, et al. ∙

research

∙ 01/05/2021

Learning Accurate Dense Correspondences and When to Trust Them

Establishing dense correspondences between a pair of images is an import...

14 Prune Truong, et al. ∙

research

∙ 12/14/2020

Scaling Semantic Segmentation Beyond 1K Classes on a Single GPU

The state-of-the-art object detection and image classification methods c...

0 Shipra Jain, et al. ∙

research

∙ 12/08/2020

Accurate 3D Object Detection using Energy-Based Models

Accurate 3D object detection (3DOD) is crucial for safe navigation of co...

0 Fredrik K. Gustafsson, et al. ∙

research

∙ 12/07/2020

Learning Video Instance Segmentation with Recurrent Graph Neural Networks

Most existing approaches to video instance segmentation comprise multipl...

8 Joakim Johnander, et al. ∙

research

∙ 10/01/2020

Few-Shot Classification By Few-Iteration Meta-Learning

Learning in a low-data regime from only a few labeled examples is an imp...

35 Ardhendu Shekhar Tripathi, et al. ∙

research

∙ 09/16/2020

GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network

The feature correlation layer serves as a key neural network module in n...

1 Prune Truong, et al. ∙

research

∙ 09/15/2020

AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results

This paper reviews the AIM 2020 challenge on efficient single image supe...

6 Kai Zhang, et al. ∙

Martin Danelljan

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