We propose a single-shot approach to determining 6-DoF pose of an object with available 3D computer-aided design (CAD) model from a single RGB image. Our method, dubbed MRC-Net, comprises two stages. The first performs pose classification and renders the 3D object in the classified pose. The second stage performs regression to predict fine-grained residual pose within class. Connecting the two stages is a novel multi-scale residual correlation (MRC) layer that captures high-and-low level correspondences between the input image and rendering from first stage. MRC-Net employs a Siamese network with shared weights between both stages to learn embeddings for input and rendered images. To mitigate ambiguity when predicting discrete pose class labels on symmetric objects, we use soft probabilistic labels to define pose class in the first stage. We demonstrate state-of-the-art accuracy, outperforming all competing RGB-based methods on four challenging BOP benchmark datasets: T-LESS, LM-O, YCB-V, and ITODD. Our method is non-iterative and requires no complex post-processing. Our code and pretrained models are available at https://github.com/amzn/mrc-net-6d-pose.

A novel statistical ink drop displacement (IDD) printer model for the direct binary search (DBS) halftoning algorithm is proposed. It is intended primarily for pagewide inkjet printers that exhibit dot displacement errors. The tabular approach in the literature predicts the gray value of a printed pixel based on the halftone pattern in some neighborhood of that pixel. However, memory retrieval time and the complexity of memory requirements hamper its feasibility in printers that have a very large number of nozzles and produce ink drops that affect a large neighborhood. To avoid this problem, our IDD model embodies dot displacements by moving each perceived ink drop in the image from its nominal location to its actual location, rather than manipulating the average gray values. This enables DBS to directly compute the appearance of the final printout without retrieving values from a table. In so doing, the memory issue is eliminated and the computation efficiency is enhanced. The deterministic cost function of DBS is replaced by the expectation over the ensemble of the displacements for the proposed model such that the statistical behavior of the ink drops is accounted for. Experimental results show significant improvement in the quality of the printed image over the original DBS. Besides, the image quality obtained by the proposed approach appears to be slightly better than that obtained by the tabular approach.

Error diffusion is a popular technique widely used in desktop printers, especially inkjet printers. However, since the conventional error diffusion is computed in raster order, it produces worm artifacts in the highlights and shadows. In addition, as a serial algorithm, it limits the efficiency and flexibility of hardware implementations. To address these two issues, we propose a novel serpentine based error diffusion algorithm that uses tone dependent error weights and thresholds. We also propose an expanded error weight location matrix to improve the halftone quality in the extreme tones. With this new algorithm, we achieve better halftones comparing to the original tone dependent fast error diffusion, especially in the quarter tones.

Network coding has the potential to provide powerful support to transmit real-time traffic in wireless network. In this paper, we utilize pairwise coding to schedule the flows which have heterogeneous delay constraints and weights. Our goal is to maximize the weighted sum of scheduled packets that satisfy the delay constraints. We formulate the problem as an integer linear programming problem, and propose two algorithms to solve it. The first algorithm drops the integral constraints and rounds the fractional solutions in such a way that the rounded solution is also optimal. Inspired by the first algorithm and for better running time, we propose the second algorithm based on a minimum cost flow formulation. The formulation is proved to be equivalent to the original integer linear programming formulation. Simulations are conducted to show the effectiveness of our approach over two greedy algorithms.