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Found 19 papers, 10 papers with code
Incremental Joint Learning of Depth, Pose and Implicit Scene Representation on Monocular Camera in Large-scale Scenes
For pose estimation, a feature-metric bundle adjustment (FBA) method is designed for accurate and robust camera tracking in large-scale scenes.
NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and Denoising
Second, the occupancy scene representation is replaced with Signed Distance Field (SDF) hierarchical scene representation for high-quality reconstruction and view synthesis.
Compact 3D Gaussian Splatting For Dense Visual SLAM
Recent work has shown that 3D Gaussian-based SLAM enables high-quality reconstruction, accurate pose estimation, and real-time rendering of scenes.
PLGSLAM: Progressive Neural Scene Represenation with Local to Global Bundle Adjustment
To this end, we introduce PLGSLAM, a neural visual SLAM system capable of high-fidelity surface reconstruction and robust camera tracking in real-time.
ProSGNeRF: Progressive Dynamic Neural Scene Graph with Frequency Modulated Auto-Encoder in Urban Scenes
Implicit neural representation has demonstrated promising results in view synthesis for large and complex scenes.
Improving Image Captioning via Predicting Structured Concepts
Having the difficulty of solving the semantic gap between images and texts for the image captioning task, conventional studies in this area paid some attention to treating semantic concepts as a bridge between the two modalities and improved captioning performance accordingly.
Vesper: A Compact and Effective Pretrained Model for Speech Emotion Recognition
Although PTMs shed new light on artificial general intelligence, they are constructed with general tasks in mind, and thus, their efficacy for specific tasks can be further improved.
Emergent Bio-Functional Similarities in a Cortical-Spike-Train-Decoding Spiking Neural Network Facilitate Predictions of Neural Computation
Despite its better bio-plausibility, goal-driven spiking neural network (SNN) has not achieved applicable performance for classifying biological spike trains, and showed little bio-functional similarities compared to traditional artificial neural networks.
DWFormer: Dynamic Window transFormer for Speech Emotion Recognition
Self-attention mechanism is applied within windows for capturing temporal important information locally in a fine-grained way.
SpeechFormer++: A Hierarchical Efficient Framework for Paralinguistic Speech Processing
Paralinguistic speech processing is important in addressing many issues, such as sentiment and neurocognitive disorder analyses.
Multi-Attention Network for Compressed Video Referring Object Segmentation
To address this problem, we propose a multi-attention network which consists of dual-path dual-attention module and a query-based cross-modal Transformer module.
Ranked #5 on
Referring Expression Segmentation
on A2D Sentences
Unsupervised Learning of Monocular Depth and Ego-Motion Using Multiple Masks
A new unsupervised learning method of depth and ego-motion using multiple masks from monocular video is proposed in this paper.
LSSED: a large-scale dataset and benchmark for speech emotion recognition
Speech emotion recognition is a vital contributor to the next generation of human-computer interaction (HCI).
Ranked #1 on
Speech Emotion Recognition
on LSSED
Domain-invariant Similarity Activation Map Contrastive Learning for Retrieval-based Long-term Visual Localization
Visual localization is a crucial component in the application of mobile robot and autonomous driving.
Sex Differences in Severity and Mortality Among Patients With COVID-19: Evidence from Pooled Literature Analysis and Insights from Integrated Bioinformatic Analysis
Objective: To conduct a meta-analysis of current studies that examined sex differences in severity and mortality in patients with COVID-19, and identify potential mechanisms underpinning these differences.
Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing Environments
To retrieve a target image from the database, the query image is first encoded using the encoder belonging to the query domain to obtain a domain-invariant feature vector.
Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning
In this work, we propose to train CNNs from images annotated with multiple tags, to enhance the quality of visual representation of the trained CNN model.
Tagging like Humans: Diverse and Distinct Image Annotation
In D2IA, we generate a relevant and distinct tag subset, in which the tags are relevant to the image contents and semantically distinct to each other, using sequential sampling from a determinantal point process (DPP) model.
Saliency Fusion in Eigenvector Space with Multi-Channel Pulse Coupled Neural Network
Saliency computation has become a popular research field for many applications due to the useful information provided by saliency maps.
