Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs). XXIV. 54 New Quasars and Candidate Obscured Quasars at $5.71 le z le 7.02$

Kavli Affiliate: John D. Silverman | First 5 Authors: Yoshiki Matsuoka, Yoshiki Matsuoka, , , | Summary: We present spectroscopic identification of 43 quasars and 11 candidate obscured quasars in the epoch of reionization (EoR) at $5.71 le z le 7.02$, along with 29 galaxies at similar redshifts. This is the 24th publication from the […]


Continue.. Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs). XXIV. 54 New Quasars and Candidate Obscured Quasars at $5.71 le z le 7.02$

Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs). XXIV. 54 New Quasars and Candidate Obscured Quasars at $5.71 le z le 7.02$

Kavli Affiliate: John D. Silverman | First 5 Authors: Yoshiki Matsuoka, Yoshiki Matsuoka, , , | Summary: We present spectroscopic identification of 43 quasars and 11 candidate obscured quasars in the epoch of reionization (EoR) at $5.71 le z le 7.02$, along with 29 galaxies at similar redshifts. This is the 24th publication from the […]


Continue.. Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs). XXIV. 54 New Quasars and Candidate Obscured Quasars at $5.71 le z le 7.02$

Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs). XXIV. 54 New Quasars and Candidate Obscured Quasars at $5.71 le z le 7.02$

Kavli Affiliate: John D. Silverman | First 5 Authors: Yoshiki Matsuoka, Yoshiki Matsuoka, , , | Summary: We present spectroscopic identification of 43 quasars and 11 candidate obscured quasars in the epoch of reionization (EoR) at $5.71 le z le 7.02$, along with 29 galaxies at similar redshifts. This is the 24th publication from the […]


Continue.. Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs). XXIV. 54 New Quasars and Candidate Obscured Quasars at $5.71 le z le 7.02$

RadGS-Reg: Registering Spine CT with Biplanar X-rays via Joint 3D Radiative Gaussians Reconstruction and 3D/3D Registration

Kavli Affiliate: Feng Wang | First 5 Authors: Ao Shen, Ao Shen, , , | Summary: Computed Tomography (CT)/X-ray registration in image-guided navigation remains challenging because of its stringent requirements for high accuracy and real-time performance. Traditional "render and compare" methods, relying on iterative projection and comparison, suffer from spatial information loss and domain gap. […]


Continue.. RadGS-Reg: Registering Spine CT with Biplanar X-rays via Joint 3D Radiative Gaussians Reconstruction and 3D/3D Registration

Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation

Kavli Affiliate: Feng Yuan | First 5 Authors: Yifan Gao, Yifan Gao, , , | Summary: Foundation models pre-trained on large-scale natural image datasets offer a powerful paradigm for medical image segmentation. However, effectively transferring their learned representations for precise clinical applications remains a challenge. In this work, we propose Dino U-Net, a novel encoder-decoder […]


Continue.. Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation

AdaDPCC: Adaptive Rate Control and Rate-Distortion-Complexity Optimization for Dynamic Point Cloud Compression

Kavli Affiliate: Wei Gao | First 5 Authors: Chenhao Zhang, Chenhao Zhang, , , | Summary: Dynamic point cloud compression (DPCC) is crucial in applications like autonomous driving and AR/VR. Current compression methods face challenges with complexity management and rate control. This paper introduces a novel dynamic coding framework that supports variable bitrate and computational […]


Continue.. AdaDPCC: Adaptive Rate Control and Rate-Distortion-Complexity Optimization for Dynamic Point Cloud Compression

Learned Rate Control for Frame-Level Adaptive Neural Video Compression via Dynamic Neural Network

Kavli Affiliate: Wei Gao | First 5 Authors: Chenhao Zhang, Chenhao Zhang, , , | Summary: Neural Video Compression (NVC) has achieved remarkable performance in recent years. However, precise rate control remains a challenge due to the inherent limitations of learning-based codecs. To solve this issue, we propose a dynamic video compression framework designed for […]


Continue.. Learned Rate Control for Frame-Level Adaptive Neural Video Compression via Dynamic Neural Network

Traversing the Narrow Path: A Two-Stage Reinforcement Learning Framework for Humanoid Beam Walking

Kavli Affiliate: Wei Gao | First 5 Authors: TianChen Huang, TianChen Huang, , , | Summary: Traversing narrow paths is challenging for humanoid robots due to the sparse and safety-critical footholds required. Purely template-based or end-to-end reinforcement learning-based methods suffer from such harsh terrains. This paper proposes a two stage training framework for such narrow […]


Continue.. Traversing the Narrow Path: A Two-Stage Reinforcement Learning Framework for Humanoid Beam Walking

Traversing the Narrow Path: A Two-Stage Reinforcement Learning Framework for Humanoid Beam Walking

Kavli Affiliate: Wei Gao | First 5 Authors: TianChen Huang, TianChen Huang, , , | Summary: Traversing narrow beams is challenging for humanoids due to sparse, safety-critical contacts and the fragility of purely learned policies. We propose a physically grounded, two-stage framework that couples an XCoM/LIPM footstep template with a lightweight residual planner and a […]


Continue.. Traversing the Narrow Path: A Two-Stage Reinforcement Learning Framework for Humanoid Beam Walking