Context-TAP: Tracking Any Point Demands Spatial Context Features

We tackle the problem of Tracking Any Point (TAP) in videos, which specifically aims at estimating persistent long-term trajectories of query points in videos. Previous methods attempted to estimate these trajectories independently to incorporate longer image sequences, therefore, ignoring the potential benefits of incorporating spatial context features. We argue that independent video point tracking also demands spatial context features. To this end, we propose a novel framework Context-TAP, which effectively improves point trajectory accuracy by aggregating spatial context features in videos. Context-TAP contains two main modules: 1) a SOurse Feature Enhancement (SOFE) module, and 2) a TArget Feature Aggregation (TAFA) module. Context-TAP significantly improves PIPs all-sided, reducing 11.4% Average Trajectory Error of Occluded Points (ATE-Occ) on CroHD and increasing 11.8% Average Percentage of Correct Keypoint (A-PCK) on TAP-Vid-Kinectics. Demos are available at this $\href{https://wkbian.github.io/Projects/Context-TAP/}{webpage}$.Comment: Project Page: this $\href{https://wkbian.github.io/Projects/Context-TAP/}{webpage}

NeuralMarker: A Framework for Learning General Marker Correspondence

We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker. Conventionally, this problem is addressed by fitting a homography model based on sparse feature matching. However, they are only able to handle plane-like markers and the sparse features do not sufficiently utilize appearance information. In this paper, we propose a novel framework NeuralMarker, training a neural network estimating dense marker correspondences under various challenging conditions, such as marker deformation, harsh lighting, etc. Besides, we also propose a novel marker correspondence evaluation method circumstancing annotations on real marker-image pairs and create a new benchmark. We show that NeuralMarker significantly outperforms previous methods and enables new interesting applications, including Augmented Reality (AR) and video editing.Comment: Accepted by ToG (SIGGRAPH Asia 2022). Project Page: https://drinkingcoder.github.io/publication/neuralmarker

VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation

We introduce VideoFlow, a novel optical flow estimation framework for videos. In contrast to previous methods that learn to estimate optical flow from two frames, VideoFlow concurrently estimates bi-directional optical flows for multiple frames that are available in videos by sufficiently exploiting temporal cues. We first propose a TRi-frame Optical Flow (TROF) module that estimates bi-directional optical flows for the center frame in a three-frame manner. The information of the frame triplet is iteratively fused onto the center frame. To extend TROF for handling more frames, we further propose a MOtion Propagation (MOP) module that bridges multiple TROFs and propagates motion features between adjacent TROFs. With the iterative flow estimation refinement, the information fused in individual TROFs can be propagated into the whole sequence via MOP. By effectively exploiting video information, VideoFlow presents extraordinary performance, ranking 1st on all public benchmarks. On the Sintel benchmark, VideoFlow achieves 1.649 and 0.991 average end-point-error (AEPE) on the final and clean passes, a 15.1% and 7.6% error reduction from the best-published results (1.943 and 1.073 from FlowFormer++). On the KITTI-2015 benchmark, VideoFlow achieves an F1-all error of 3.65%, a 19.2% error reduction from the best-published result (4.52% from FlowFormer++). Code is released at \url{https://github.com/XiaoyuShi97/VideoFlow}

Genome-Wide Analysis of CCA1-Like Proteins in Soybean and Functional Characterization of GmMYB138a

Plant CIRCADIAN CLOCK ASSOCIATED1 (CCA1)-like proteins are a class of single-repeat MYELOBLASTOSIS ONCOGENE (MYB) transcription factors generally featured by a highly conserved motif SHAQK(Y/F)F, which play important roles in multiple biological processes. Soybean is an important grain legume for seed protein and edible vegetable oil. However, essential understandings regarding CCA1-like proteins are very limited in soybean. In this study, 54 CCA1-like proteins were identified by data mining of soybean genome. Phylogenetic analysis indicated that soybean CCA1-like subfamily showed evolutionary conservation and diversification. These CCA1-like genes displayed tissue-specific expression patterns, and analysis of genomic organization and evolution revealed 23 duplicated gene pairs. Among them, GmMYB138a was chosen for further investigation. Our protein–protein interaction studies revealed that GmMYB138a, but not its alternatively spliced isoform, interacts with a 14-3-3 protein (GmSGF14l). Although GmMYB138a was predominately localized in nucleus, the resulting complex of GmMYB138a and GmSGF14l was almost evenly distributed in nucleus and cytoplasm, supporting that 14-3-3s interact with their clients to alter their subcellular localization. Additionally, qPCR analysis suggested that GmMYB138a and GmSGF14l synergistically or antagonistically respond to drought, cold and salt stresses. Our findings will contribute to future research in regard to functions of soybean CCA1-like subfamily, especially regulatory mechanisms of GmMYB138a in response to abiotic stresses

Review: Acetylation mechanisms and targeted therapies in cardiac fibrosis

Cardiac fibrosis is a common pathophysiological remodeling process that occurs in a variety of cardiovascular diseases and greatly influences heart structure and function, progressively leading to the development of heart failure. However, to date, few effective therapies for cardiac fibrosis exist. Abnormal proliferation, differentiation, and migration of cardiac fibroblasts are responsible for the excessive deposition of extracellular matrix in the myocardium. Acetylation, a widespread and reversible protein post-translational modification, plays an important role in the development of cardiac fibrosis by adding acetyl groups to lysine residues. Many acetyltransferases and deacetylases regulate the dynamic alterations of acetylation in cardiac fibrosis, regulating a range of pathogenic conditions including oxidative stress, mitochondrial dysfunction, and energy metabolism disturbance. In this review, we demonstrate the critical roles that acetylation modifications caused by different types of pathological injury play in cardiac fibrosis. Furthermore, we propose therapeutic acetylation-targeting strategies for the prevention and treatment of patients with cardiac fibrosis