Latest Research
NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results
lixinustc/kvq-challenge-cvpr-ntire2024
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This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected dataset KVQ from popular short-form video platform, i. e., Kuaishou/Kwai Platform.
CorrNet+: Sign Language Recognition and Translation via Spatial-Temporal Correlation
In specific, CorrNet+ employs a correlation module and an identification module to build human body trajectories.
Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System
ghdtjr/a-llmrec
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Despite their effectiveness under cold scenarios, we observe that they underperform simple traditional collaborative filtering models under warm scenarios due to the lack of collaborative knowledge.
Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty
In this paper, we propose a novel framework called Hyper-Evidential Neural Network (HENN) that explicitly models predictive uncertainty due to composite class labels in training data in the context of the belief theory called Subjective Logic (SL).
VG4D: Vision-Language Model Goes 4D Video Recognition
By transferring the knowledge of the VLM to the 4D encoder and combining the VLM, our VG4D achieves improved recognition performance.
Closely Interactive Human Reconstruction with Proxemics and Physics-Guided Adaption
Specifically, we first design a latent representation based on Vector Quantised-Variational AutoEncoder (VQ-VAE) to model human interaction.
Consistency Training by Synthetic Question Generation for Conversational Question Answering
In our novel model-agnostic approach, referred to as CoTaH (Consistency-Trained augmented History), we augment the historical information with synthetic questions and subsequently employ consistency training to train a model that utilizes both real and augmented historical data to implicitly make the reasoning robust to irrelevant history.
JointViT: Modeling Oxygen Saturation Levels with Joint Supervision on Long-Tailed OCTA
The oxygen saturation level in the blood (SaO2) is crucial for health, particularly in relation to sleep-related breathing disorders.
Sampling-based Pseudo-Likelihood for Membership Inference Attacks
In this study, we propose a Sampling-based Pseudo-Likelihood (\textbf{SPL}) method for MIA (\textbf{SaMIA}) that calculates SPL using only the text generated by an LLM to detect leaks.
FairSSD: Understanding Bias in Synthetic Speech Detectors
In this work, we examine bias in existing synthetic speech detectors to determine if they will unfairly target a particular gender, age and accent group.
