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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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07/12/2023
A Comprehensive Overview of Large Language Models
Large Language Models (LLMs) have shown excellent generalization capabil...
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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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03/20/2023
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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12/05/2022
PointCaM: Cut-and-Mix for Open-Set Point Cloud Analysis
Point cloud analysis is receiving increasing attention, however, most ex...
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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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10/11/2022
Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning
Zero-Shot Learning (ZSL) models aim to classify object classes that are ...
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06/21/2022
Vicinity Vision Transformer
Vision transformers have shown great success on numerous computer vision...
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04/12/2022
Towards Open-Set Object Detection and Discovery
With the human pursuit of knowledge, open-set object detection (OSOD) ha...
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11/28/2021
Learning To Segment Dominant Object Motion From Watching Videos
Existing deep learning based unsupervised video object segmentation meth...
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11/24/2021
PU-Transformer: Point Cloud Upsampling Transformer
Given the rapid development of 3D scanners, point clouds are becoming po...
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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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08/16/2021
PnP-3D: A Plug-and-Play for 3D Point Clouds
With the help of the deep learning paradigm, many point cloud networks h...
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06/25/2021
Energy-Based Generative Cooperative Saliency Prediction
Conventional saliency prediction models typically learn a deterministic ...
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06/22/2021
Confidence-Aware Learning for Camouflaged Object Detection
Confidence-aware learning is proven as an effective solution to prevent ...
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04/20/2021
Transformer Transforms Salient Object Detection and Camouflaged Object Detection
The transformer networks, which originate from machine translation, are ...
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04/15/2021
Learning structure-aware semantic segmentation with image-level supervision
Compared with expensive pixel-wise annotations, image-level labels make ...
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04/06/2021
Weakly Supervised Video Salient Object Detection
Significant performance improvement has been achieved for fully-supervis...
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03/12/2021
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion
Given the prominence of current 3D sensors, a fine-grained analysis on t...
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03/06/2021
Simultaneously Localize, Segment and Rank the Camouflaged Objects
Camouflage is a key defence mechanism across species that is critical to...
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02/26/2021
Recursive Training for Zero-Shot Semantic Segmentation
General purpose semantic segmentation relies on a backbone CNN network t...
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02/06/2021
Robust normalizing flows using Bernstein-type polynomials
Normalizing flows (NFs) are a class of generative models that allows exa...
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12/10/2020
Uncertainty-Aware Deep Calibrated Salient Object Detection
Existing deep neural network based salient object detection (SOD) method...
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12/01/2020
3D Guided Weakly Supervised Semantic Segmentation
Pixel-wise clean annotation is necessary for fully-supervised semantic s...
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11/25/2020
How to train your conditional GAN: An approach using geometrically structured latent manifolds
Conditional generative modeling typically requires capturing one-to-many...
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10/07/2020
Conditional Generative Modeling via Learning the Latent Space
Although deep learning has achieved appealing results on several machine...
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10/05/2020
Attention Guided Semantic Relationship Parsing for Visual Question Answering
Humans explain inter-object relationships with semantic labels that demo...
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09/07/2020
Uncertainty Inspired RGB-D Saliency Detection
We propose the first stochastic framework to employ uncertainty for RGB-...
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07/23/2020
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection
In this paper, we propose a noise-aware encoder-decoder framework to dis...
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05/14/2020
Dense-Resolution Network for Point Cloud Classification and Segmentation
Point cloud analysis is attracting attention from Artificial Intelligenc...
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04/26/2020
Attention Prior for Real Image Restoration
Deep convolutional neural networks perform better on images containing s...
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03/24/2020
A Systematic Evaluation: Fine-Grained CNN vs. Traditional CNN Classifiers
To make the best use of the underlying minute and subtle differences, fi...
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03/20/2020
How to Train Your Event Camera Neural Network
Event cameras are paradigm-shifting novel sensors that report asynchrono...
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03/16/2020
Any-Shot Object Detection
Previous work on novel object detection considers zero or few-shot setti...
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01/20/2020
Accuracy vs. Complexity: A Trade-off in Visual Question Answering Models
Visual Question Answering (VQA) has emerged as a Visual Turing Test to v...
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12/04/2019
Spectral-GANs for High-Resolution 3D Point-cloud Generation
Point-clouds are a popular choice for vision and graphics tasks due to t...
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11/30/2019
Representation Learning on Unit Ball with 3D Roto-Translational Equivariance
Convolution is an integral operation that defines how the shape of one f...
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11/28/2019
Geometric Feedback Network for Point Cloud Classification
As the basic task of point cloud learning, classification is fundamental...
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08/24/2019
Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes
Existing networks directly learn feature representations on 3D point clo...
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08/09/2019
Question-Agnostic Attention for Visual Question Answering
Visual Question Answering (VQA) models employ attention mechanisms to di...
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06/28/2019
Densely Residual Laplacian Super-Resolution
Super-Resolution convolutional neural networks have recently demonstrate...
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06/09/2019
Unsupervised Primitive Discovery for Improved 3D Generative Modeling
3D shape generation is a challenging problem due to the high-dimensional...
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04/24/2019
CED: Color Event Camera Dataset
Event cameras are novel, bio-inspired visual sensors, whose pixels outpu...
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04/16/2019
A Deep Journey into Super-resolution: A survey
Deep convolutional networks based super-resolution is a fast-growing fie...
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04/16/2019
Real Image Denoising with Feature Attention
Deep convolutional neural networks perform better on images containing s...
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01/03/2019
Volumetric Convolution: Automatic Representation Learning in Unit Ball
Convolution is an efficient technique to obtain abstract feature represe...
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12/02/2018
Computing Spatial Image Convolutions for Event Cameras
Spatial convolution is arguably the most fundamental of 2D image process...
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11/30/2018
From Known to the Unknown: Transferring Knowledge to Answer Questions about Novel Visual and Semantic Concepts
Current Visual Question Answering (VQA) systems can answer intelligent q...
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11/22/2018
Polarity Loss for Zero-shot Object Detection
Zero-shot object detection is an emerging research topic that aims to re...
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11/01/2018