Search Results for author:
Found 11 papers, 5 papers with code
Role Play: Learning Adaptive Role-Specific Strategies in Multi-Agent Interactions
It trains a common policy with role embedding observations and employs a role predictor to estimate the joint role embeddings of other agents, helping the learning agent adapt to its assigned role.
Large Vision-Language Models as Emotion Recognizers in Context Awareness
Extensive experiments and analyses demonstrate that LVLMs achieve competitive performance in the CAER task across different paradigms.
Asynchronous Multimodal Video Sequence Fusion via Learning Modality-Exclusive and -Agnostic Representations
To tackle these issues, we propose a Multimodal fusion approach for learning modality-Exclusive and modality-Agnostic representations (MEA) to refine multimodal features and leverage the complementarity across distinct modalities.
PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications
In the parameter-efficient secondary SFT phase, a mixture of universal-specific experts strategy is presented to resolve the competency conflict between medical generalist and pediatric expertise mastery.
Towards Multimodal Sentiment Analysis Debiasing via Bias Purification
In the inference phase, given a factual multimodal input, MCIS imagines two counterfactual scenarios to purify and mitigate these biases.
CPR-Coach: Recognizing Composite Error Actions based on Single-class Training
For the first time, this paper constructs a vision-based system to complete error action recognition and skill assessment in CPR.
AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perception
Driver distraction has become a significant cause of severe traffic accidents over the past decade.
Context De-confounded Emotion Recognition
However, a long-overlooked issue is that a context bias in existing datasets leads to a significantly unbalanced distribution of emotional states among different context scenarios.
CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in Space
Considering that the pose estimator is sensitive to background interference, this paper proposes a counterfactual analysis framework named CASpaceNet to complete robust 6D pose estimation of the spaceborne targets under complicated background.
A Survey of Video-based Action Quality Assessment
Most of the existing work focuses on sports and medical care.
TSA-Net: Tube Self-Attention Network for Action Quality Assessment
Specifically, we introduce a single object tracker into AQA and propose the Tube Self-Attention Module (TSA), which can efficiently generate rich spatio-temporal contextual information by adopting sparse feature interactions.
