11 accepted papers
Vision-Language Models (VLMs) like CLIP struggle to understand negation, often embedding affirmatives and negatives similarly (e.g., matching "no dog" with dog images). Existing methods refine negation understanding via fine-tuning CLIP’s text encoder, risking overfitting. In this work, we propose C
Despite significant advancements in the research of aquatic-aerial robots, existing configurations struggle to efficiently perform underwater, surface, and aerial movement. In this paper, we propose a novel multimodal surfing aquatic-aerial vehicle, SurfAAV, which efficiently integrates underwater n…
Semantic segmentation is a key technique that enables mobile robots to understand and navigate surrounding environments autonomously. However, most existing works focus on segmenting known objects, overlooking the identification of unknown classes, which is common in real-world applications. In this
Morphological differences and dense spatial relations of organs make multi-organ segmentation challenging. Current segmentation networks, primarily based on CNNs and Transformers, represent organs by aggregating information within fixed regions. However, aggregated representations often fail to accu…
Multimodal 3D object detectors leverage the strengths of both geometry-aware LiDAR point clouds and semantically rich RGB images to enhance detection performance. However, the inherent heterogeneity between these modalities, including unbalanced convergence and modal misalignment, poses significant
High-precision dense object detection in retail is crucial for automation, inventory management, and sales optimization. Our experiments revealed that detection models perform significantly better with frontal views than with oblique views, motivating the development of RecNet. RecNet utilizes a Rec…
Despite significant advancements in the research of aquatic-aerial robots, existing configurations struggle to efficiently perform underwater, surface, and aerial movement. In this paper, we propose a novel multimodal surfing aquaticaerial vehicle, SurfAAV, which efficiently integrates underwater na
To defend against personalized generation, a new form of infringement that is more concealed and destructive, the existing copyright protection methods is to add adversarial perturbations in images. However, these methods focus solely on countering illegal personalization, neglecting the requirement…
Fast and accurate path planning is important for ground robots to achieve safe and efficient autonomous navigation in unstructured outdoor environments. However, most existing methods exploiting either 2D or 2.5D maps struggle to balance the efficiency and safety for ground robots navigating in such…
The registration of point clouds is a key ingredient of LiDAR-based SLAM systems and mapping approaches. A challenging task in this context is finding the right data association between 3D points. This paper proposes a novel and flexible graph network architecture to tackle the keypoint matching pro
In this paper, we address the problem of combining 3D laser scanner and camera information to estimate the motion of a mobile platform. We propose a direct laser-visual odometry approach building upon photometric image alignment. Our approach is designed to maximize the information usage of both, th…