5 citations · 15 across the 13 of their papers we have counts for
13 papers
All rivers run into the sea: Unified Modality Brain-like Emotional Central Mechanism
Xinji Mai, Junxiong Lin, Haoran Wang +10
In the field of affective computing, fully leveraging information from a variety of sensory modalities is essential for the comprehensive understanding and processing of human emot…
From Efficient Multimodal Models to World Models: A Survey
Xinji Mai, Zeng Tao, Junxiong Lin +5
Multimodal Large Models (MLMs) are becoming a significant research focus, combining powerful large language models with multimodal learning to perform complex tasks across differen…
OneTracker: Unifying Visual Object Tracking with Foundation Models and Efficient Tuning
Lingyi Hong, Shilin Yan, Renrui Zhang +8
Visual object tracking aims to localize the target object of each frame based on its initial appearance in the first frame. Depending on the input modility, tracking tasks can be d…
OneVOS: Unifying Video Object Segmentation with All-in-One Transformer Framework
Wanyun Li, Pinxue Guo, Xinyu Zhou +5
Contemporary Video Object Segmentation (VOS) approaches typically consist stages of feature extraction, matching, memory management, and multiple objects aggregation. Recent advanc…
ClickVOS: Click Video Object Segmentation
Pinxue Guo, Lingyi Hong, Xinyu Zhou +7
Video Object Segmentation (VOS) task aims to segment objects in videos. However, previous settings either require time-consuming manual masks of target objects at the first frame d…
Align-DFER: Pioneering Comprehensive Dynamic Affective Alignment for Dynamic Facial Expression Recognition with CLIP
Zeng Tao, Yan Wang, Junxiong Lin +9
The performance of CLIP in dynamic facial expression recognition (DFER) task doesn't yield exceptional results as observed in other CLIP-based classification tasks. While CLIP's pr…