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Found 9 papers, 4 papers with code
MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition
In addition to expanding the dataset size, we introduce a new track around open-vocabulary emotion recognition.
Exploring the Transferability of Visual Prompting for Multimodal Large Language Models
To achieve this, we propose Transferable Visual Prompting (TVP), a simple and effective approach to generate visual prompts that can transfer to different models and improve their performance on downstream tasks after trained on only one model.
Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wild
Multimodal fusion is a significant method for most multimodal tasks.
Decentralized Stochastic Subgradient Methods for Nonsmooth Nonconvex Optimization
Furthermore, we establish that our proposed framework encompasses a wide range of existing efficient decentralized subgradient methods, including decentralized stochastic subgradient descent (DSGD), DSGD with gradient-tracking technique (DSGD-T), and DSGD with momentum (DSGDm).
Direct Motif Extraction from High Resolution Crystalline STEM Images
The results are a representation of the motif in form of an image, atomic positions, primitive unit cell vectors, and a denoised and a modeled reconstruction of the input image.
NEPHELE: A Neural Platform for Highly Realistic Cloud Radiance Rendering
Using such a cloud platform compatible with neural rendering, we further showcase the capabilities of our cloud radiance rendering through a series of applications, ranging from cloud VR/AR rendering.
Probability-Dependent Gradient Decay in Large Margin Softmax
Based on the analysis results, we can provide evidence that the large margin Softmax will affect the local Lipschitz constraint of the loss function by regulating the probability-dependent gradient decay rate.
Towards Hyperparameter-free Policy Selection for Offline Reinforcement Learning
How to select between policies and value functions produced by different training algorithms in offline reinforcement learning (RL) -- which is crucial for hyperpa-rameter tuning -- is an important open question.
Microphone Array Generalization for Multichannel Narrowband Deep Speech Enhancement
This paper addresses the problem of microphone array generalization for deep-learning-based end-to-end multichannel speech enhancement.
