19 accepted papers
Back injuries resulting from manual material handling have long constituted a prominent threat to occupational safety. While back-support exosuits offer the potential to augment human strength, their practical implementation is hindered by persistent challenges pertaining to comfort and safety. Draw…
Video anomaly detection (VAD) aims to detect anomalies that deviate from what is expected. In open-world scenarios, the expected events may change as requirements change. For example, not wearing a mask may be considered abnormal during a flu outbreak but normal otherwise. However, existing methods…
Text-to-Image generation (TTI) technologies are advancing rapidly, especially in the English language communities. However, apart from the user input language barrier problem, English-native TTI models inherently carry biases from their English world centric training data, which creates a dilemma fo…
Deep learning-based object detection methods have shown significant success, particularly in robotic vision tasks like autonomous navigation and object manipulation. However, their performance drops sharply in low-light conditions, challenging robots in poorly lit environments. To address this, we p
Diffusion Models (DMs) have evolved into advanced image generation tools, especially for few-shot fine-tuning where a pretrained DM is fine-tuned on a small set of images to capture specific styles or objects. Many people upload these personalized checkpoints online, fostering communities such as Ci…
In this paper, we propose a unified layout planning and image generation model, PlanGen, which can pre-plan spatial layout conditions before generating images as shown in Figure 1. Unlike previous diffusion-based models that treat layout planning and layout-to-image as two separate models, PlanGen j…
The distributed nature of federated learning exposes it to significant security threats, among which backdoor attacks are one of the most prevalent. However, existing backdoor attacks face a trade-off between attack strength and stealthiness: attacks maximizing the attack strength are often detectab…
LLMs have shown impressive progress in natural language processing. However, they still face significant challenges in TableQA, where real-world complexities such as diverse table structures, multilingual data, and domain-specific reasoning are crucial. Existing TableQA benchmarks are often limited
Diffusion models build a new milestone for image generation yet raising public concerns, for they can be fine-tuned on unauthorized images for customization. Protection based on adversarial attacks rises to encounter this unauthorized diffusion customization, by adding protective watermarks to image…
Body weight support (BWS) systems are extensively utilized in rehabilitation robots to deliver sophisticated unloading force (i.e., vertical interaction force) for gravity and impedance compensation. The robust and accurate unloading force rendering is critical for gait training. In this letter, a c
Large Language Models are typically trained on datasets collected from the web, which may inadvertently contain harmful or sensitive personal information. To address growing privacy concerns, unlearning methods have been proposed to remove the influence of specific data from trained models. Of these…
Diffusion Models (DMs) have evolved into advanced image generation tools especially for few-shot generation where a pre-trained model is fine-tuned on a small set of images to capture a specific style or object. Despite their success concerns exist about potential copyright violations stemming from…
Enhancing the stability of machine learning algorithms under distributional shifts is at the heart of the Out-of-Distribution (OOD) Generalization problem. Derived from causal learning, recent works of invariant learning pursue strict invariance with multiple training environments. Although intuitiv…
The task of layout-to-image generation involves synthesizing images based on the captions of objects and their spatial positions. Existing methods still struggle in complex layout generation, where common bad cases include object missing, inconsistent lighting, conflicting view angles, etc. To effec…
While generative diffusion models excel in producing high-quality images, they can also be misused to mimic authorized images, posing a significant threat to AI systems. Efforts have been made to add calibrated perturbations to protect images from diffusion-based mimicry pipelines. However, most of…
Recently, Diffusion Models (DMs) boost a wave in AI for Art yet raise new copyright concerns, where infringers benefit from using unauthorized paintings to train DMs and generate novel paintings in a similar style. To address these emerging copyright violations, in this paper, we are the first to ex…
Generating the heatmaps is one of the explanation methods to show what regions the model use to predict in vision tasks. GradCAM is a popular approach to provide such heatmaps. However, GradCAM is post-hoc, and its heatmaps are not always meeting human annotations. Inspired by CGC (Contrastive GradC…
Most human activities in daily living or professional work rely on upper body motion. Measuring upper body motion is essential for many applications such as health evaluation, rehabilitation, human power augmentation, skill transferring, etc. Computer vision-based systems have been widely used to di…
Humanoid robots can imitate human behaviour and provide interactive services to humans due to their humanoid form, especially humanoid wheeled robots that can perform more complex tasks with the additional mobility. With the development of robotics technology, humanoid robots have been used increasi