Hierarchical Masked 3D Diffusion Model for Video Outpainting

Video outpainting aims to adequately complete missing areas at the edges of video frames. Compared to image outpainting, it presents an additional challenge as the model should maintain the temporal consistency of the filled area. In this paper, we introduce a masked 3D diffusion model for video outpainting. We use the technique of mask modeling to train the 3D diffusion model. This allows us to use multiple guide frames to connect the results of multiple video clip inferences, thus ensuring temporal consistency and reducing jitter between adjacent frames. Meanwhile, we extract the global frames of the video as prompts and guide the model to obtain information other than the current video clip using cross-attention. We also introduce a hybrid coarse-to-fine inference pipeline to alleviate the artifact accumulation problem. The existing coarse-to-fine pipeline only uses the infilling strategy, which brings degradation because the time interval of the sparse frames is too large. Our pipeline benefits from bidirectional learning of the mask modeling and thus can employ a hybrid strategy of infilling and interpolation when generating sparse frames. Experiments show that our method achieves state-of-the-art results in video outpainting tasks. More results are provided at our https://fanfanda.github.io/M3DDM/.Comment: ACM MM 2023 accepte

Electrophoretic deposition and laser cladding of bioglass coating on Ti

Bioglass coatings derived from electrophoretic deposition method were fused on Ti surface by laser cladding process using a continuous CO laser. The specimens were studied by field-emission scanning electron microscopy, X-ray diffraction and bonding tests. Titanium oxide layer with hierarchical structures consisting of submicron rows of leaf-like embossments and nano-pores was obtained by combining acid etching and anodization processes, which increased the surface roughness of Ti. When heat-treatment temperature was 700 °C and high, CaSiO phase began to crystallize from the bioglass matrix and the crystallinity reached its maximum at 700 °C. During the electrophoretic deposition process, porous bioglass coatings composed of bioglass particles and fibers were deposited on Ti surface. Bioglass coatings with similar hierarchical structure containing submillimeter bioglass beads and microfibers were synthesized on Ti surface by laser fusion. There are no obvious microcracks at the interface of the Ti-coating, which revealed the good bonding between Ti-porcelain. With the laser scanning distance decreased, the bond strength increased accordingly. After only one day immersion in SBF, calcium phosphate began to precipitate on the bioglass coating's surfaces. The thickness of the calcium phosphate precipitation and the amount of microparticles increased with immersion time

A 3D Relative-Motion Context Constraint-Based MAP Solution for Multiple-Object Tracking Problems

Multi-object tracking (MOT), especially by using a moving monocular camera, is a very challenging task in the field of visual object tracking. To tackle this problem, the traditional tracking-by-detection-based method is heavily dependent on detection results. Occlusion and mis-detections will often lead to tracklets or drifting. In this paper, the tasks of MOT and camera motion estimation are formulated as finding a maximum a posteriori (MAP) solution of joint probability and synchronously solved in a unified framework. To improve performance, we incorporate the three-dimensional (3D) relative-motion model into a sequential Bayesian framework to track multiple objects and the camera’s ego-motion estimation. A 3D relative-motion model that describes spatial relations among objects is exploited for predicting object states robustly and recovering objects when occlusion and mis-detections occur. Reversible jump Markov chain Monte Carlo (RJMCMC) particle filtering is applied to solve the posteriori estimation problem. Both quantitative and qualitative experiments with benchmark datasets and video collected on campus were conducted, which confirms that the proposed method is outperformed in many evaluation metrics

Apoptosis and Metabolism of Mesenchymal Stem Cells during Chondrogenic Differentiation In Vitro

Abstract : Transplantation of mesenchymal stem cells (MSCs) is often used to treat cartilage defects, due to the lack of intrinsic self-healing capacity of this non-vascularized tissue. Nevertheless, it is extremely challenging to fully differentiate MSCs to chondrocytes, in particular the articular chondrocyte lineage, as well as maintain stable chondrogenic phenotype during ex vivo expansion. Cellular apoptosis and metabolism are important factors that influence the process of chondrogenesis, which have largely been overlooked. For example, lowered metabolism as a result of hypoxia enhances chondrogenic differentiation of MSCs, whilst inhibiting osteogenesis. It is also known that the regulation of apoptosis has a profound influence on chondrocyte hypertrophy during chondrogenesis. The focus of this review is therefore to critically examine the influence of apoptosis and cellular metabolism on chondrogenic differentiation of MSCs

Synergistic effects of adaptive reward and reinforcement learning rules on cooperation

Cooperative behavior in multi-agent systems has been a focal point of research, particularly in the context of pairwise interaction games. While previous studies have successfully used reinforcement learning rules to explain and predict the behavior of agents in two-agent interactions, multi-agent interactions are more complex, and the impact of reward mechanisms on agent behavior is often overlooked. To address this gap, we propose a framework that combines the public goods game (PGG) with reinforcement learning and adaptive reward mechanisms to better capture decision-making behavior in multi-agent interactions. In that, PGG is adopted to reflect the decision-making behavior of multi-agent interactions, self-regarding Q -learning emphasizes an experience-based strategy update, and adaptive reward focuses on the adaptability. We are mainly concentrating on the synergistic effects of them. The simulations demonstrate that while self-regarding Q -learning fails to prevent the collapse of cooperation in the traditional PGG, the fraction of cooperation increases significantly when the adaptive reward strategy is included. Meanwhile, the theoretical analyses aligned with our simulation results, which revealed that there is a specific reward cost required to maximize the fraction of cooperation. Overall, this study provides a novel perspective on establishing cooperative reward mechanisms in social dilemmas and highlights the importance of considering adaptive reward mechanisms in multi-agent interactions

Structure design, fabrication, properties of laminated ceramics: A review

Various methods exist to improve the toughness and reduce the sensitivity to the defects in ceramic materials; however, the bionic laminated ceramics are the most promising ones. In this paper, we review preparation, sintering, properties and toughening mechanisms of laminated ceramics. Delamination cracks and crack deflection are the main sources of energy dissipation during the fracture of laminated ceramics with weak interfaces. The increasing fracture toughness is due to the residual compressive stress and is the mechanism of laminated ceramics toughness with strong interfaces. These extensively studied laminated ceramics with excellent comprehensive performances (such as high temperature resistance, ablation resistance, thermal shock resistance, high thermal conductivity and impact resistance) have broadened the scope of potential and useful engineering applications. This paper also predicts the feasibility of complex structural 3D designs for rapid prototyping as well as aid development of the new sintering technology, such as cold sintering process and liquid silicon infiltration process, for the preparation of laminated ceramics. Keywords: Laminated ceramics, Properties, Toughening mechanism, Applicatio