9 accepted papers
General robotic grasping systems require accurate object affordance perception in diverse open-world scenarios following human instructions. However, current studies suffer from the problem of lacking reasoning-based large-scale affordance prediction data, leading to considerable concern about open-…
Single-view clothed human reconstruction has emerged as a prominent research focus, yet reconstructing the occluded backside of the human body remains a significant challenge due to viewpoint limitations and occlusion. In this paper, we propose a novel single-view clothed human reconstruction method…
X-ray 3D reconstruction has achieved superior performance in medical imaging with traditional and deep learning methods. However, when sparse-view X-ray projections are used to minimize patient exposure to radiation, these methods tend to overfit and produce blurring. To overcome this problem, we pr…
Topology reasoning, which unifies perception and structured reasoning, plays a vital role in understanding intersections for autonomous driving. However, its performance heavily relies on the accuracy of lane detection, particularly at connected lane endpoints. Existing methods often suffer from lan…
Most existing reflection removal methods pay too much attention to the transmission layer and ignore the mutual complementary mechanisms between the transmission layer and the reflection layer. To make full use of the complementarity and distinction between the reflection and transmission layers in…
As an emerging task that integrates perception and reasoning, topology reasoning in autonomous driving scenes has recently garnered widespread attention. However, existing work often emphasizes "perception over reasoning": they typically boost reasoning performance by enhancing the perception of la…
Monocular 6D pose estimation is a fundamental task in computer vision. Existing works often adopt a twostage pipeline by establishing correspondences and utilizing a RANSAC algorithm to calculate 6 degrees-of-freedom (6DoF) pose. Recent works try to integrate differentiable RANSAC algorithms to achi…
Due to inevitable noises and quantization error, the reconstructed 3D models via RGB-D sensors always accompany geometric error and camera drifting, which consequently lead to blurring and unnatural texture mapping results. Most of the 3D reconstruction methods focus on either geometry refinement or…
Acquiring realistic texture details for 3D models is important in 3D reconstruction. However, the existence of geometric errors, caused by noisy RGB-D sensor data, always makes the color images cannot be accurately aligned onto reconstructed 3D models. In this paper, we propose a global-to-local cor…