9 accepted papers
Multi-Agent Discussion (MAD) has garnered increasing attention very recently, where multiple LLM instances collaboratively solve problems via structured discussion. However, we find that current MAD methods easily suffer from discussion inconsistency—LLMs fail to reach a coherent solution—due to the…
Visual Speech Recognition (VSR), commonly known as lipreading, enables the recognition of spoken text by analyzing lip visual features. Due to the subtlety of lip movements, its recognition is much harder than other motion recognition tasks. Existing VSR models face the challenge of viseme ambiguit
In controllable image generation, synthesizing coherent and consistent images from multiple reference inputs, i.e., **Multi-Image Composition** (MICo), remains a challenging problem, partly hindered by the lack of high-quality training data.To bridge this gap, we conduct a systematic study of MICo,
Continuous prediction in complex environments is critical for Unmanned Aerial Vehicle (UAV). However, the existing Vision-Language Navigation (VLN) models follows the dead-reckoning, which iteratively predicts the next waypoint and updates its position, thereby constructing the complete trajectory. …
Despite impressive advancements in video understanding, most efforts remain limited to coarse-grained or visual-only video tasks. However, real-world videos encompass omni-modal information (vision, audio, and speech) with a series of events forming a cohesive storyline. The lack of multi-modal vide…
Recent advancements in large video-language models have revolutionized video understanding tasks. However, their efficiency is significantly constrained by processing high volumes of visual tokens. Existing token compression strategies apply a fixed compression ratio, ignoring the variability in sem
The acquisition of targets' complete point cloud model is crucial for tasks such as 3D reconstruction and disordered grasping. Shooting targets from multiple perspectives and registering point clouds from different perspectives can obtain a relatively complete point cloud model. However, small scene
"Large vision-language models (LVLMs) have shown promising performance on a variety of vision-language tasks. However, they remain susceptible to hallucinations, generating outputs misaligned with visual content or instructions. While various mitigation strategies have been proposed, they often negl…
Image-to-text generation aims to describe images using natural language. Recently, zero-shot image captioning based on pre-trained vision-language models (VLMs) and large language models (LLMs) has made significant progress. However, we have observed and empirically demonstrated that these methods a…