7 accepted papers
Generating large-scale demonstrations for dexterous manipulation remains a challenging problem, and various approaches have been proposed in recent years to address it. Among these, generative models have emerged as a promising paradigm, enabling the efficient generation of diverse and plausible dem…
We present PAVE, a framework for adapting pre-trained video large language models (Video-LLMs) to downstream tasks that incorporate side-channel signals, such as audio, camera pose, or high frame rate videos. PAVE introduces a lightweight adaptation strategy called "patching", which adds a small num…
We aim to recover the geometry of 3D parametric scenes using very few depth measurements from low-cost, commercially available time-of-flight sensors. These sensors offer very low spatial resolution (i.e., a single pixel), but image a wide field-of-view per pixel and capture detailed time-of-flight…
Despite the general capabilities of Large Language Models (LLMs) like GPT-4, these models still request fine-tuning or adaptation with customized data when meeting the specific business demands and intricacies of tailored use cases. However, this process inevitably introduces new safety threats, par…
Diffusion Purification, purifying noised images with diffusion models, has been widely used for enhancing certified robustness via randomized smoothing. However, existing frameworks often grapple with the balance between efficiency and effectiveness. While the Denoising Diffusion Probabilistic Model…
We present a method for reconstructing 3D shape of arbitrary Lambertian objects based on measurements by miniature energy-efficient low-cost single-photon cameras. These cameras operating as time resolved image sensors illuminate the scene with a very fast pulse of diffuse light and record the shape…
The success rate of current adversarial attacks remains low on real-world 3D face recognition tasks because the 3D-printing attacks need to meet the requirement that the generated points should be adjacent to the surface, which limits the adversarial example' searching space. Additionally, they have…