8 accepted papers
State Space Models (SSMs) have emerged as efficient alternatives to attention for vision tasks, offering linear-time sequence processing with competitive accuracy. Vision SSMs, however, require serializing 2D images into 1D token sequences along a predefined scan order, a factor often overlooked. We…
Color constancy methods often struggle to generalize across different camera sensors due to varying spectral sensitivities. We present GCC, which leverages diffusion models to inpaint color checkers into images for illumination estimation. Our key innovations include (1) a single-step deterministic…
When users give natural language instructions to service robots, positional information is often referenced relative to objects in the environment rather than absolute coordinates. However, humans naturally use relative references. For example, in“Go to the chair and pick up empty bottles”, where th
We present SpectroMotion, a novel approach that combines 3D Gaussian Splatting (3DGS) with physically-based rendering (PBR) and deformation fields to reconstruct dynamic specular scenes. Previous methods extending 3DGS to model dynamic scenes have struggled to represent specular surfaces accurately.…
As robots are widely used in assisting manual tasks, an interesting challenge is: Can mobile robots help create a labeled knowledge dataset that can be used for efficiently creating deep learning models for other sensors? This paper proposes an Unsupervised Person Labeling and Identification (UPLIFT…
Person identification and tracking (PIT) is an essential issue in computer vision and robotic applications. It has long been studied and achieved by technologies such as RFID or face/fingerprint/iris recognition. These approaches, however, have their limitations due to environmental constraints (suc…
Advanced Internet of Things (IoT) techniques have made human-environment interaction much easier. Existing solutions usually enable such interactions without knowing the identities of action performers. However, identifying users who are interacting with environments is a key to enable personalized…
Person identification (PID) is a key issue in many IoT applications. It has long been studied and achieved by technologies such as RFID and face/fingerprint/iris recognition. These approaches, however, have their limitations due to environmental constraints (such as lighting and obstacles) or requir…