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08/16/2023
Improving Audio-Visual Segmentation with Bidirectional Generation
The aim of audio-visual segmentation (AVS) is to precisely differentiate...
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08/11/2023
Image-based Geolocalization by Ground-to-2.5D Map Matching
We study the image-based geolocalization problem that aims to locate gro...
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08/08/2023
All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation
In this work, we propose a new transformer-based regularization to bette...
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07/27/2023
Scaling TransNormer to 175 Billion Parameters
We present TransNormerLLM, the first linear attention-based Large Langua...
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07/19/2023
Exploring Transformer Extrapolation
Length extrapolation has attracted considerable attention recently since...
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07/18/2023
Linearized Relative Positional Encoding
Relative positional encoding is widely used in vanilla and linear transf...
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05/08/2023
Toeplitz Neural Network for Sequence Modeling
Sequence modeling has important applications in natural language process...
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05/02/2023
An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation Problems
The Segment Anything Model (SAM) has demonstrated exceptional performanc...
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03/27/2023
Fine-grained Audible Video Description
We explore a new task for audio-visual-language modeling called fine-gra...
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03/20/2023
Learning Audio-Visual Source Localization via False Negative Aware Contrastive Learning
Self-supervised audio-visual source localization aims to locate sound-so...
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03/04/2023
Improving Audio-Visual Video Parsing with Pseudo Visual Labels
Audio-Visual Video Parsing is a task to predict the events that occur in...
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10/19/2022
The Devil in Linear Transformer
Linear transformers aim to reduce the quadratic space-time complexity of...
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10/15/2022
Linear Video Transformer with Feature Fixation
Vision Transformers have achieved impressive performance in video classi...
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07/28/2022
Neural Architecture Search on Efficient Transformers and Beyond
Recently, numerous efficient Transformers have been proposed to reduce t...
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07/26/2022
AMF: Adaptable Weighting Fusion with Multiple Fine-tuning for Image Classification
Fine-tuning is widely applied in image classification tasks as a transfe...
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07/25/2022
Deep Laparoscopic Stereo Matching with Transformers
The self-attention mechanism, successfully employed with the transformer...
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06/21/2022
Vicinity Vision Transformer
Vision transformers have shown great success on numerous computer vision...
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03/29/2022
Locality Matters: A Locality-Biased Linear Attention for Automatic Speech Recognition
Conformer has shown a great success in automatic speech recognition (ASR...
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03/14/2022
Implicit Motion Handling for Video Camouflaged Object Detection
We propose a new video camouflaged object detection (VCOD) framework tha...
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02/17/2022
cosFormer: Rethinking Softmax in Attention
Transformer has shown great successes in natural language processing, co...
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12/17/2021
Transcribing Natural Languages for The Deaf via Neural Editing Programs
This work studies the task of glossification, of which the aim is to em ...
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11/29/2021
MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation
The task of semi-supervised video object segmentation (VOS) has been gre...
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09/15/2021
RGB-D Saliency Detection via Cascaded Mutual Information Minimization
Existing RGB-D saliency detection models do not explicitly encourage RGB...
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06/24/2021
Depth-Guided Camouflaged Object Detection
Camouflaged object detection (COD) aims to segment camouflaged objects h...
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06/16/2021
Invertible Attention
Attention has been proved to be an efficient mechanism to capture long-r...
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05/27/2021
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding
Single-image super-resolution (SR) and multi-frame SR are two ways to su...
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04/01/2021
Deep Two-View Structure-from-Motion Revisited
Two-view structure-from-motion (SfM) is the cornerstone of 3D reconstruc...
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04/01/2021
Positive Sample Propagation along the Audio-Visual Event Line
Visual and audio signals often coexist in natural environments, forming ...
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03/07/2021
ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring
Video deblurring models exploit consecutive frames to remove blurs from ...
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12/06/2020
Depth Completion using Piecewise Planar Model
A depth map can be represented by a set of learned bases and can be effi...
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12/02/2020
Efficient Depth Completion Using Learned Bases
In this paper, we propose a new global geometry constraint for depth com...
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12/01/2020
Displacement-Invariant Cost Computation for Efficient Stereo Matching
Although deep learning-based methods have dominated stereo matching lead...
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10/28/2020
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation
Learning matching costs has been shown to be critical to the success of ...
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10/26/2020
Hierarchical Neural Architecture Search for Deep Stereo Matching
To reduce the human efforts in neural network design, Neural Architectur...
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04/04/2020
Deblurring by Realistic Blurring
Existing deep learning methods for image deblurring typically train mode...
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04/08/2019
Noise-Aware Unsupervised Deep Lidar-Stereo Fusion
In this paper, we present LidarStereoNet, the first unsupervised Lidar-s...
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04/08/2019
Unsupervised Deep Epipolar Flow for Stationary or Dynamic Scenes
Unsupervised deep learning for optical flow computation has achieved pro...
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08/27/2018
Stereo Computation for a Single Mixture Image
This paper proposes an original problem of stereo computation from a sin...
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08/13/2018
3D Geometry-Aware Semantic Labeling of Outdoor Street Scenes
This paper is concerned with the problem of how to better exploit 3D geo...
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08/12/2018
Open-World Stereo Video Matching with Deep RNN
Deep Learning based stereo matching methods have shown great successes a...
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03/28/2018
Adversarial Spatio-Temporal Learning for Video Deblurring
Camera shake or target movement often leads to undesired blur effects in...
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09/04/2017
Self-Supervised Learning for Stereo Matching with Self-Improving Ability
Exiting deep-learning based dense stereo matching methods often rely on ...
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03/01/2016
