Vary: Scaling up the vision vocabulary for large vision-language models
Modern Large Vision-Language Models (LVLMs) enjoy the same vision vocabulary--CLIP,
which can cover most common vision tasks. However, for some special vision task that …
which can cover most common vision tasks. However, for some special vision task that …
Small language model meets with reinforced vision vocabulary
Playing Large Vision Language Models (LVLMs) in 2023 is trendy among the AI community.
However, the relatively large number of parameters (more than 7B) of popular LVLMs makes …
However, the relatively large number of parameters (more than 7B) of popular LVLMs makes …
OneChart: Purify the Chart Structural Extraction via One Auxiliary Token
Chart parsing poses a significant challenge due to the diversity of styles, values, texts, and
so forth. Even advanced large vision-language models (LVLMs) with billions of parameters …
so forth. Even advanced large vision-language models (LVLMs) with billions of parameters …
MotionLLM: Understanding Human Behaviors from Human Motions and Videos
This study delves into the realm of multi-modality (ie, video and motion modalities) human
behavior understanding by leveraging the powerful capabilities of Large Language Models …
behavior understanding by leveraging the powerful capabilities of Large Language Models …
Uncertainty-boosted Robust Video Activity Anticipation
Video activity anticipation aims to predict what will happen in the future, embracing a broad
application prospect ranging from robot vision and autonomous driving. Despite the recent …
application prospect ranging from robot vision and autonomous driving. Despite the recent …
Self-Supervised Visual Preference Alignment
This paper makes the first attempt towards unsupervised preference alignment in Vision-
Language Models (VLMs). We generate chosen and rejected responses with regard to the …
Language Models (VLMs). We generate chosen and rejected responses with regard to the …
Is a 3D-Tokenized LLM the Key to Reliable Autonomous Driving?
Rapid advancements in Autonomous Driving (AD) tasks turned a significant shift toward end-
to-end fashion, particularly in the utilization of vision-language models (VLMs) that integrate …
to-end fashion, particularly in the utilization of vision-language models (VLMs) that integrate …
Emotion Recognition from Videos Using Multimodal Large Language Models
Abstract The diffusion of Multimodal Large Language Models (MLLMs) has opened new
research directions in the context of video content understanding and classification. Emotion …
research directions in the context of video content understanding and classification. Emotion …