Concerns with enabling computers to interpret and understand visual inputs, such as images and videos.
The article by Qiuhao Li and Shenghai Yuan examines the refinement of the Jacquard Grasp Dataset. The researchers propose the use of a Human-In-The-Loop (HIL) method to improve the dataset’s…
Continue readingThe article introduces UAV-Rain1k, a new benchmark dataset for removing raindrops from unmanned aerial vehicle (UAV) images. The researchers created the dataset to address the lack of focus on raindrop…
Continue readingThe study presents a new framework for Class-incremental learning (CIL), specifically for Long-Tailed Class-Incremental Learning (LT-CIL). The proposed Task-aware Expandable (TaE) framework dynamically allocates and updates task-specific trainable parameters, learning…
Continue readingAvatarMMC presents a new method for generating and editing 3D head avatars. The approach uses a 3D Generative Adversarial Network (GAN) and a Latent Diffusion Model (LDM) for multi-modal conditioning….
Continue readingInkSight is a project aiming to bridge the gap between traditional pen-and-paper note-taking and digital note-taking. It allows users to convert their physical handwritten notes (offline handwriting) into a digital…
Continue readingThe article presents an efficient network for Low-Light Image Enhancement (LLIE) named Horizontal/Vertical-Intensity (HVI) and Color and Intensity Decoupling Network (CIDNet). Traditional methods use Deep Neural Networks (DNNs) in sRGB…
Continue readingThis paper presents a new privacy-preserving synthetic continual semantic segmentation framework for robotic surgery. The researchers address the problem of ‘catastrophic forgetting’ in Deep Neural Networks (DNNs), which refers to…
Continue readingThe article introduces a novel approach to long-context video understanding using a memory-consolidated vision transformer (MC-ViT). Standard transformer-based video encoders struggle with long-contexts due to their quadratic complexity. The researchers…
Continue readingThis article presents a new approach to learn geometries such as depth and surface normal from images. The introduced method, called Adaptive Surface Normal (ASN) constraint, extracts geometric context that…
Continue readingThe paper discusses CREMA, a modality-fusion framework aimed at enhancing the efficiency of multimodal compositional video reasoning. This framework is designed to integrate any new modality into video reasoning, leveraging…
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