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Found 8 papers, 1 papers with code
Precise Event Spotting in Sports Videos: Solving Long-Range Dependency and Class Imbalance
Particularly, we propose a network with a convolutional spatial-temporal feature extractor enhanced with our proposed Adaptive Spatio-Temporal Refinement Module (ASTRM) and a long-range temporal module.
Open-Set Object Detection By Aligning Known Class Representations
Open-Set Object Detection (OSOD) has emerged as a contemporary research direction to address the detection of unknown objects.
Cross-Modal Fusion and Attention Mechanism for Weakly Supervised Video Anomaly Detection
Recently, weakly supervised video anomaly detection (WS-VAD) has emerged as a contemporary research direction to identify anomaly events like violence and nudity in videos using only video-level labels.
Beyond Few-shot Object Detection: A Detailed Survey
While traditional FSOD methods have been studied before, this survey paper comprehensively reviews FSOD research with a specific focus on covering different FSOD settings such as standard FSOD, generalized FSOD, incremental FSOD, open-set FSOD, and domain adaptive FSOD.
Fiducial Focus Augmentation for Facial Landmark Detection
To effectively utilize the newly proposed augmentation technique, we employ a Siamese architecture-based training mechanism with a Deep Canonical Correlation Analysis (DCCA)-based loss to achieve collective learning of high-level feature representations from two different views of the input images.
Ranked #1 on
Facial Landmark Detection
on WFLW
(FR@10 (inter-ocular) metric)
Revisiting Class Imbalance for End-to-end Semi-Supervised Object Detection
Semi-supervised object detection (SSOD) has made significant progress with the development of pseudo-label-based end-to-end methods.
M2FNet: Multi-modal Fusion Network for Emotion Recognition in Conversation
We introduce a new feature extractor to extract latent features from the audio and visual modality.
Ranked #15 on
Emotion Recognition in Conversation
on MELD
Learned Smartphone ISP on Mobile NPUs with Deep Learning, Mobile AI 2021 Challenge: Report
As the quality of mobile cameras starts to play a crucial role in modern smartphones, more and more attention is now being paid to ISP algorithms used to improve various perceptual aspects of mobile photos.
