DiffDreamer: Consistent Single-view Perpetual View Generation with Conditional Diffusion Models

Perpetual view generation -- the task of generating long-range novel views by flying into a given image -- has been a novel yet promising task. We introduce DiffDreamer, an unsupervised framework capable of synthesizing novel views depicting a long camera trajectory while training solely on internet-collected images of nature scenes. We demonstrate that image-conditioned diffusion models can effectively perform long-range scene extrapolation while preserving both local and global consistency significantly better than prior GAN-based methods. Project page: https://primecai.github.io/diffdreamer

Learning Object-Centric Neural Scattering Functions for Free-viewpoint Relighting and Scene Composition

Photorealistic object appearance modeling from 2D images is a constant topic in vision and graphics. While neural implicit methods (such as Neural Radiance Fields) have shown high-fidelity view synthesis results, they cannot relight the captured objects. More recent neural inverse rendering approaches have enabled object relighting, but they represent surface properties as simple BRDFs, and therefore cannot handle translucent objects. We propose Object-Centric Neural Scattering Functions (OSFs) for learning to reconstruct object appearance from only images. OSFs not only support free-viewpoint object relighting, but also can model both opaque and translucent objects. While accurately modeling subsurface light transport for translucent objects can be highly complex and even intractable for neural methods, OSFs learn to approximate the radiance transfer from a distant light to an outgoing direction at any spatial location. This approximation avoids explicitly modeling complex subsurface scattering, making learning a neural implicit model tractable. Experiments on real and synthetic data show that OSFs accurately reconstruct appearances for both opaque and translucent objects, allowing faithful free-viewpoint relighting as well as scene composition. Project website: https://kovenyu.com/osf/Comment: Project website: https://kovenyu.com/osf/ Journal extension of arXiv:2012.08503. The first two authors contributed equally to this wor

ZeroNVS: Zero-Shot 360-Degree View Synthesis from a Single Real Image

We introduce a 3D-aware diffusion model, ZeroNVS, for single-image novel view synthesis for in-the-wild scenes. While existing methods are designed for single objects with masked backgrounds, we propose new techniques to address challenges introduced by in-the-wild multi-object scenes with complex backgrounds. Specifically, we train a generative prior on a mixture of data sources that capture object-centric, indoor, and outdoor scenes. To address issues from data mixture such as depth-scale ambiguity, we propose a novel camera conditioning parameterization and normalization scheme. Further, we observe that Score Distillation Sampling (SDS) tends to truncate the distribution of complex backgrounds during distillation of 360-degree scenes, and propose "SDS anchoring" to improve the diversity of synthesized novel views. Our model sets a new state-of-the-art result in LPIPS on the DTU dataset in the zero-shot setting, even outperforming methods specifically trained on DTU. We further adapt the challenging Mip-NeRF 360 dataset as a new benchmark for single-image novel view synthesis, and demonstrate strong performance in this setting. Our code and data are at http://kylesargent.github.io/zeronvs/Comment: 17 page

State of the Art on Diffusion Models for Visual Computing

The field of visual computing is rapidly advancing due to the emergence of generative artificial intelligence (AI), which unlocks unprecedented capabilities for the generation, editing, and reconstruction of images, videos, and 3D scenes. In these domains, diffusion models are the generative AI architecture of choice. Within the last year alone, the literature on diffusion-based tools and applications has seen exponential growth and relevant papers are published across the computer graphics, computer vision, and AI communities with new works appearing daily on arXiv. This rapid growth of the field makes it difficult to keep up with all recent developments. The goal of this state-of-the-art report (STAR) is to introduce the basic mathematical concepts of diffusion models, implementation details and design choices of the popular Stable Diffusion model, as well as overview important aspects of these generative AI tools, including personalization, conditioning, inversion, among others. Moreover, we give a comprehensive overview of the rapidly growing literature on diffusion-based generation and editing, categorized by the type of generated medium, including 2D images, videos, 3D objects, locomotion, and 4D scenes. Finally, we discuss available datasets, metrics, open challenges, and social implications. This STAR provides an intuitive starting point to explore this exciting topic for researchers, artists, and practitioners alike

Development of a Fused Deposition Modeling System for Low Melting Temperature Metal Alloys

This research focused on extending the applications of fused deposition modeling (FDM) by extrusion and deposition of low melting temperature metal alloys to create threedimensional metal structures and single-layer contacts which may prove useful for electronic interconnects. Six commercially available low melting temperature solder alloys (Bi36Pb32Sn31Ag1, Bi58Sn42, Sn63Pb37, Sn50Pb50, Sn60Bi40, Sn96.5Ag3.5) were tested for the creation of a fused deposition modeling for metals (FDMm) system with special attention given to Sn-Bi solders. An existing FDM 3000 was used and two alloys were successfully extruded through the system's extrusion head. Deposition was achieved through specific modifications to system toolpath commands and a comparison of solders with eutectic and non-eutectic compositions is discussed. The modifications demonstrate the ability to extrude simple single-layer solder lines with varying thicknesses, including sharp 90 deg angles and smooth curved lines and showing the possibility of using this system for printed circuit board applications in which various connections need to be processed. Deposition parameters altered for extrusion and the deposition results of low melting temperature metal alloys are introduced

Quality of life for men with metastatic castrate-resistant prostate cancer participating in an aerobic and resistance exercise pilot intervention

Background: Following a prostate cancer diagnosis, disease and treatment-related symptoms may result in diminished quality of life (QoL). Whether exercise improves QoL in men with metastatic castrate-resistant prostate cancer (mCRPC) is not fully understood. Methods: We conducted a 3-arm pilot randomized controlled trial to assess the feasibility, acceptability, safety, and efficacy of a 12-week remotely monitored exercise program among men with mCRPC. Here we report qualitative changes in QoL, consistent with the guidelines for pilot trials. Men were randomized to control, aerobic exercise, or resistance exercise. Exercise prescriptions were based on baseline cardiorespiratory and strength assessments. QoL outcomes were evaluated using self-reported questionnaires (e.g., QLQ-C30, PROMIS Fatigue, Pittsburgh Sleep Quality Index (PSQI), EPIC-26) collected at baseline and 12 weeks. Results: A total of 25 men were randomized (10 control, 8 aerobic, 7 resistance). Men were predominately white (76 %) with a median age of 71 years (range: 51 – 84) and 10.5 years (range: 0.9 – 26.3) post prostate cancer diagnosis. The men reported poor sleep quality and high levels of fatigue at enrollment. Other baseline QoL metrics were relatively high. Compared to the controls at 12 weeks, the resistance arm reported some improvements in social function and urinary irritative/obstruction symptoms while the aerobic arm reported some improvements in social function and urinary incontinence, yet worsening nausea/vomiting. Compared to the resistance arm, the aerobic arm reported worse urinary irritative/obstruction symptoms and self-rated QoL, yet some improvements in emotional function, insomnia, and diarrhea. Conclusions: The 3-month exercise intervention pilot appeared to have modest effects on QoL among mCRPC survivors on ADT. Given the feasibility, acceptability, and safety demonstrated in prior analyses, evaluation of the effect of the intervention on QoL in a larger sample and for extended duration may still be warranted

Effect of ramucirumab on ALBI grade in patients with advanced HCC: Results from REACH and REACH-2

Background & Aims: The albumin-bilirubin (ALBI) grade/score is derived from a validated nomogram to objectively assess prognosis and liver function in patients with hepatocellular carcinoma (HCC). In this post hoc analysis, we assessed prognosis in terms of survival by baseline ALBI grade and monitored liver function during treatment with ramucirumab or placebo using the ALBI score in patients with advanced HCC. Methods: Patients with advanced HCC, Child-Pugh class A with prior sorafenib treatment were randomised in REACH trials to receive ramucirumab 8 mg/kg or placebo every 2weeks. Datawere analysed by trial and as a meta-analysis of individual patientlevel data (pooled population) from REACH (alpha-fetoprotein>− 400 ng/ml) and REACH-2. Patients from REACHwith Child-Pugh class Bwere analysed as a separate cohort. The ALBI grades and scoreswere calculated at baseline and before each treatment cycle. Results: Baseline characteristics by ALBI grade were balanced between treatment arms among patients in the pooled population (ALBI-1, n = 231; ALBI-2, n = 296; ALBI-3, n = 7). Baseline ALBI grade was prognostic for overall survival (OS; ALBI grade 2 vs. 1; hazard ratio [HR]: 1.38 [1.13-1.69]), after adjusting for other significant prognostic factors. Mean ALBI scores remained stable in both treatment arms compared with baseline and were unaffected by baseline ALBI grade, macrovascular invasion, tumour response, geographical region, or prior locoregional therapy. Baseline ALBI grades 2 and 3 were associated with increased incidence of liver-specific adverse events and discontinuation rates in both treatments. Ramucirumab improved OS in patients with baseline ALBI grade 1 (HR 0.605 [0.445-0.824]) and ALBI grade 2 (HR 0.814 [0.630-1.051]. Conclusions: Compared with placebo, ramucirumab did not negatively impact liver function and improved survival irrespective of baseline ALBI grade