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08/23/2023
MolGrapher: Graph-based Visual Recognition of Chemical Structures
The automatic analysis of chemical literature has immense potential to a...
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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...
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07/20/2023
Cascade-DETR: Delving into High-Quality Universal Object Detection
Object localization in general environments is a fundamental part of vis...
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07/05/2023
Prompting Diffusion Representations for Cross-Domain Semantic Segmentation
While originally designed for image generation, diffusion models have re...
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07/03/2023
Segment Anything Meets Point Tracking
The Segment Anything Model (SAM) has established itself as a powerful ze...
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04/30/2023
StyleGenes: Discrete and Efficient Latent Distributions for GANs
We propose a discrete latent distribution for Generative Adversarial Net...
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03/28/2023
Mask-Free Video Instance Segmentation
The recent advancement in Video Instance Segmentation (VIS) has largely ...
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03/22/2023
NeRF-GAN Distillation for Memory-Efficient 3D-Aware Generation with Convolutions
Pose-conditioned convolutional generative models struggle with high-qual...
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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 ...
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10/10/2022
Fast Hierarchical Learning for Few-Shot Object Detection
Transfer learning based approaches have recently achieved promising resu...
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08/18/2022
ManiFlow: Implicitly Representing Manifolds with Normalizing Flows
Normalizing Flows (NFs) are flexible explicit generative models that hav...
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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...
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07/28/2022
Video Mask Transfiner for High-Quality Video Instance Segmentation
While Video Instance Segmentation (VIS) has seen rapid progress, current...
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07/26/2022
Tracking Every Thing in the Wild
Current multi-category Multiple Object Tracking (MOT) metrics use class ...
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04/05/2022
Arbitrary-Scale Image Synthesis
Positional encodings have enabled recent works to train a single adversa...
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03/21/2022
Transforming Model Prediction for Tracking
Optimization based tracking methods have been widely successful by integ...
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03/21/2022
Robust Visual Tracking by Segmentation
Estimating the target extent poses a fundamental challenge in visual obj...
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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...
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03/08/2022
Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences
We propose Probabilistic Warp Consistency, a weakly-supervised learning ...
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02/17/2022
Adiabatic Quantum Computing for Multi Object Tracking
Multi-Object Tracking (MOT) is most often approached in the tracking-by-...
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02/03/2022
Fast Online Video Super-Resolution with Deformable Attention Pyramid
Video super-resolution (VSR) has many applications that pose strict caus...
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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...
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01/17/2022
Collapse by Conditioning: Training Class-conditional GANs with Limited Data
Class-conditioning offers a direct means of controlling a Generative Adv...
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12/17/2021
Efficient Visual Tracking with Exemplar Transformers
The design of more complex and powerful neural network models has signif...
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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...
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11/26/2021
Mask Transfiner for High-Quality Instance Segmentation
Two-stage and query-based instance segmentation methods have achieved re...
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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...
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10/22/2021
Learning Proposals for Practical Energy-Based Regression
Energy-based models (EBMs) have experienced a resurgence within machine ...
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10/07/2021
Dense Gaussian Processes for Few-Shot Segmentation
Few-shot segmentation is a challenging dense prediction task, which enta...
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09/28/2021
PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
Establishing robust and accurate correspondences between a pair of image...
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09/10/2021
TADA: Taxonomy Adaptive Domain Adaptation
Traditional domain adaptation addresses the task of adapting a model to ...
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08/18/2021
Deep Reparametrization of Multi-Frame Super-Resolution and Denoising
We propose a deep reparametrization of the maximum a posteriori formulat...
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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...
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06/22/2021
Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation
Multiple object tracking and segmentation requires detecting, tracking, ...
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06/07/2021
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
This paper reviews the NTIRE2021 challenge on burst super-resolution. Gi...
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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 ...
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04/07/2021
Warp Consistency for Unsupervised Learning of Dense Correspondences
The key challenge in learning dense correspondences lies in the lack of ...
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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...
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03/30/2021
Deep Gaussian Processes for Few-Shot Segmentation
Few-shot segmentation is a challenging task, requiring the extraction of...
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01/26/2021
Deep Burst Super-Resolution
While single-image super-resolution (SISR) has attracted substantial int...
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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...
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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 ...
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01/05/2021
Local Memory Attention for Fast Video Semantic Segmentation
We propose a novel neural network module that transforms an existing sin...
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01/05/2021
Learning Accurate Dense Correspondences and When to Trust Them
Establishing dense correspondences between a pair of images is an import...
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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...
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12/08/2020
Accurate 3D Object Detection using Energy-Based Models
Accurate 3D object detection (3DOD) is crucial for safe navigation of co...
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12/07/2020
Learning Video Instance Segmentation with Recurrent Graph Neural Networks
Most existing approaches to video instance segmentation comprise multipl...
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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...
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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...
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09/15/2020
