Object Detection Difficulty: Suppressing Over-aggregation for Faster and Better Video Object Detection

Current video object detection (VOD) models often encounter issues with over-aggregation due to redundant aggregation strategies, which perform feature aggregation on every frame. This results in suboptimal performance and increased computational complexity. In this work, we propose an image-level Object Detection Difficulty (ODD) metric to quantify the difficulty of detecting objects in a given image. The derived ODD scores can be used in the VOD process to mitigate over-aggregation. Specifically, we train an ODD predictor as an auxiliary head of a still-image object detector to compute the ODD score for each image based on the discrepancies between detection results and ground-truth bounding boxes. The ODD score enhances the VOD system in two ways: 1) it enables the VOD system to select superior global reference frames, thereby improving overall accuracy; and 2) it serves as an indicator in the newly designed ODD Scheduler to eliminate the aggregation of frames that are easy to detect, thus accelerating the VOD process. Comprehensive experiments demonstrate that, when utilized for selecting global reference frames, ODD-VOD consistently enhances the accuracy of Global-frame-based VOD models. When employed for acceleration, ODD-VOD consistently improves the frames per second (FPS) by an average of 73.3% across 8 different VOD models without sacrificing accuracy. When combined, ODD-VOD attains state-of-the-art performance when competing with many VOD methods in both accuracy and speed. Our work represents a significant advancement towards making VOD more practical for real-world applications.Comment: 11 pages, 6 figures, accepted by ACM MM202

Parallel Acceleration and Improvement of Gravitational Field Optimization Algorithm

The Gravitational Field Algorithm, a modern optimization algorithm, mainly simulates celestial mechanics and is derived from the Solar Nebular Disk Model (SNDM). It simulates the process of planetary formation to search for the optimal solution. Although this optimization algorithm has more advantages than other optimization algorithms in multi-peak optimization problems, it still has the shortcoming of long computation time when dealing with large-scale datasets or solving complex problems. Therefore, it is necessary to improve the efficiency of the Gravitational Field Algorithm (GFA). In this paper, an optimization method based on multi-population parallel is proposed to accelerate the Gravitational Field Algorithm. With the help of the parallel mechanism in MATLAB, the algorithm execution speed will be improved by using the parallel computing mode of multi-core CPU. In addition, this paper also improves the absorption operation strategy. By comparing the experimental results of eight classical unconstrained optimization problems, it is shown that the computational efficiency of this method is improved compared with the original Gravitational Field Algorithm, and the algorithm accuracy has also been slightly improved

2-[(5-Amino-3-methyl-1-phenyl-1H-pyrazol-4-yl)(4-chloro­phen­yl)meth­yl]malononitrile

In the crystal structure of the title compound, C20H16ClN5, the dihedral angle between the pyrazole ring and the phenyl ring is 54.7 (1)° and that between the pyrazole ring and the chloro-substituted phenyl ring is 72.4 (1)°. The methyl H atoms are disordered over two positions with site occupancy factors of ca 0.7 and 0.3. One amino H is disordered equally over two positions. In the crystal structure, the mol­ecules are linked via inter­molecular N—H⋯N hydrogen bonding

Multiple Unpinned Dirac Points in Group-Va Single-layers with Phosphorene Structure

Emergent Dirac fermion states underlie many intriguing properties of graphene, and the search for them constitute one strong motivation to explore two-dimensional (2D) allotropes of other elements. Phosphorene, the ultrathin layers of black phosphorous, has been a subject of intense investigations recently, and it was found that other group-Va elements could also form 2D layers with similar puckered lattice structure. Here, by a close examination of their electronic band structure evolution, we discover two types of Dirac fermion states emerging in the low-energy spectrum. One pair of (type-I) Dirac points is sitting on high-symmetry lines, while two pairs of (type-II) Dirac points are located at generic $k$-points, with different anisotropic dispersions determined by the reduced symmetries at their locations. Such fully-unpinned (type-II) 2D Dirac points are discovered for the first time. In the absence of spin-orbit coupling, we find that each Dirac node is protected by the sublattice symmetry from gap opening, which is in turn ensured by any one of three point group symmetries. The spin-orbit coupling generally gaps the Dirac nodes, and for the type-I case, this drives the system into a quantum spin Hall insulator phase. We suggest possible ways to realize the unpinned Dirac points in strained phosphorene.Comment: 30 pages, 6 figure

Modeling the clustering in citation networks

For the study of citation networks, a challenging problem is modeling the high clustering. Existing studies indicate that the promising way to model the high clustering is a copying strategy, i.e., a paper copies the references of its neighbour as its own references. However, the line of models highly underestimates the number of abundant triangles observed in real citation networks and thus cannot well model the high clustering. In this paper, we point out that the failure of existing models lies in that they do not capture the connecting patterns among existing papers. By leveraging the knowledge indicated by such connecting patterns, we further propose a new model for the high clustering in citation networks. Experiments on two real world citation networks, respectively from a special research area and a multidisciplinary research area, demonstrate that our model can reproduce not only the power-law degree distribution as traditional models but also the number of triangles, the high clustering coefficient and the size distribution of co-citation clusters as observed in these real networks

6,7-Dihydro-4-(4-methoxy­phen­yl)-3-methyl-6-oxo-1-phenyl-1H-pyrazolo[3,4-b]pyridine-5-carbonitrile

In the title compound, C21H16N4O2, the dihedral angle between the meth­oxy-substituted benzene ring and the ring system formed by the pyridinone ring and the pyrazole ring is 57.4 (1)°, and that between the unsubstituted phenyl ring and the ring system is 135.6 (1)°. In the crystal structure, mol­ecules are linked together via inter­molecular N—H⋯O hydrogen bonds

4-(4-Bromo­phen­yl)-4,5,6,7-tetra­hydro-3-methyl-6-oxo-1-phenyl-1H-pyrazolo[3,4-b]pyridine-5-carbonitrile ethanol solvate

In the structure of the title compound, C20H15BrN4O·C2H6O, the hydrogenated pyridinone ring adopts an envelope conformation. The dihedral angle between the bromo-substituted phenyl ring and the pyrazole ring is 79.6 (1)°, and that between the non-substituted phenyl ring and the pyrazole ring is 51.2 (1)°. In the crystal structure, mol­ecules are linked via inter­molecular N—H⋯O and O—H⋯N hydrogen bonds. A short inter­molecular N⋯Br contact [3.213 (4) Å] is present in the crystal structure