RICo: Rotate-Inpaint-Complete for Generalizable Scene Reconstruction

General scene reconstruction refers to the task of estimating the full 3D geometry and texture of a scene containing previously unseen objects. In many practical applications such as AR/VR, autonomous navigation, and robotics, only a single view of the scene may be available, making the scene reconstruction a very challenging task. In this paper, we present a method for scene reconstruction by structurally breaking the problem into two steps: rendering novel views via inpainting and 2D to 3D scene lifting. Specifically, we leverage the generalization capability of large language models to inpaint the missing areas of scene color images rendered from different views. Next, we lift these inpainted images to 3D by predicting normals of the inpainted image and solving for the missing depth values. By predicting for normals instead of depth directly, our method allows for robustness to changes in depth distributions and scale. With rigorous quantitative evaluation, we show that our method outperforms multiple baselines while providing generalization to novel objects and scenes

Real-time Simultaneous Multi-Object 3D Shape Reconstruction, 6DoF Pose Estimation and Dense Grasp Prediction

Robotic manipulation systems operating in complex environments rely on perception systems that provide information about the geometry (pose and 3D shape) of the objects in the scene along with other semantic information such as object labels. This information is then used for choosing the feasible grasps on relevant objects. In this paper, we present a novel method to provide this geometric and semantic information of all objects in the scene as well as feasible grasps on those objects simultaneously. The main advantage of our method is its speed as it avoids sequential perception and grasp planning steps. With detailed quantitative analysis, we show that our method delivers competitive performance compared to the state-of-the-art dedicated methods for object shape, pose, and grasp predictions while providing fast inference at 30 frames per second speed

Chronic inflammation drives glioma growth: cellular and molecular factors responsible for an immunosuppressive microenvironment

This review examines glioma disease initiation, promotion, and progression with a focus on the cell types present within the tumor mass and the molecules responsible for the immunosuppressive microenvironment that are present at each step of the disease. The cell types and molecules present also correlate with the grade of malignancy. An overall “type 2” chronic inflammatory microenvironment develops that facilitates glioma promotion and contributes to the neo‑vascularization characteristic of gliomas. An immunosuppressive microenvironment shields the tumor mass from clearance by the patient’s own immune system. Here, we provide suggestions to deal with a chronically‑inflamed tumor microenvironment and provide recommendations to help optimize adjuvant immune and gene therapies currently offered to glioma patients

Epithelial membrane protein-2 (EMP2) promotes angiogenesis in glioblastoma multiforme.

Glioblastoma multiforme (GBM) is the most aggressive malignant brain tumor and is associated with an extremely poor clinical prognosis. One pathologic hallmark of GBM is excessive vascularization with abnormal blood vessels. Extensive investigation of anti-angiogenic therapy as a treatment for recurrent GBM has been performed. Bevacizumab, a monoclonal anti-vascular endothelial growth factor A (VEGF-A), suggests a progression-free survival benefit but no overall survival benefit. Developing novel anti-angiogenic therapies are urgently needed in controlling GBM growth. In this study, we demonstrate tumor expression of epithelial membrane protein-2 (EMP2) promotes angiogenesis both in vitro and in vivo using cell lines from human GBM. Mechanistically, this pro-angiogenic effect of EMP2 was partially through upregulating tumor VEGF-A levels. A potential therapeutic effect of a systemic administration of anti-EMP2 IgG1 on intracranial xenografts was observed resulting in both significant reduction of tumor load and decreased tumor vasculature. These results suggest the potential for anti-EMP2 IgG1 as a promising novel anti-angiogenic therapy for GBM. Further investigation is needed to fully understand the molecular mechanisms how EMP2 modulates GBM pathogenesis and progression and to further characterize anti-EMP2 therapy in GBM