arXiv subjects

Weixing Li

Publications and source records attributed to Weixing Li.

3 recordsLinked to original sources

arXiv2026

Credit the Right Box: Marginal Contribution Assignment for Structured Visual Perception

Multimodal Large Language Models (MLLMs) are increasingly expected to solve structured perception tasks that require visual recognition, language-to-object binding, object cardinality preservation, and precisely localized grounding and segmentation outputs. However, existing group-relative reinforcement learning methods provide only response-level supervision, creating a granularity mismatch for structured multi-object prediction: a single advantage is broadcast to all tokens in a response, without distinguishing individual box contributions. To address this mismatch, we propose MCR-GRPO, a marginal contribution assignment framework that derives box-level credit directly from each sampled response. Specifically, Marginal Contribution Reward (MCR) estimates each predicted box's contribution through a leave-one-out comparison, measuring how the matched set value changes when the box is removed from the response. After within-response normalization, records that improve the set value receive positive credit, while redundant or harmful ones are suppressed. To make marginal attribution stable and informative, we further introduce a Continuous Matched Set Value Evaluator that integrates permutation-invariant matching, count-aware normalization, and graded localization. MCR-GRPO maps normalized box-level marginal advantages to the token spans that generated each box, preserving GRPO's response-level comparison while enabling box-aware optimization of structured multi-object grounding. Experiments across REC, DOD, segmentation, and counting benchmarks show state-of-the-art performance over prior GRPO-based baselines.

cs.CV↗

arXiv2021

TS4Net: Two-Stage Sample Selective Strategy for Rotating Object Detection

Rotating object detection has wide applications in aerial photographs, remote sensing images, UAVs, etc. At present, most of the rotating object detection datasets focus on the field of remote sensing, and these images are usually shot in high-altitude scenes. However, image datasets captured at low-altitude areas also should be concerned, such as drone-based datasets. So we present a low-altitude dronebased dataset, named UAV-ROD, aiming to promote the research and development in rotating object detection and UAV applications. The UAV-ROD consists of 1577 images and 30,090 instances of car category annotated by oriented bounding boxes. In particular, The UAV-ROD can be utilized for the rotating object detection, vehicle orientation recognition and object counting tasks. Compared with horizontal object detection, the regression stage of the rotation detection is a tricky problem. In this paper, we propose a rotating object detector TS4Net, which contains anchor refinement module (ARM) and two-stage sample selective strategy (TS4). The ARM can convert preseted horizontal anchors into high-quality rotated anchors through twostage anchor refinement. The TS4 module utilizes different constrained sample selective strategies to allocate positive and negative samples, which is adaptive to the regression task in different stages. Benefiting from the ARM and TS4, the TS4Net can achieve superior performance for rotating object detection solely with one preseted horizontal anchor. Extensive experimental results on UAV-ROD dataset and three remote sensing datasets DOTA, HRSC2016 and UCAS-AOD demonstrate that our method achieves competitive performance against most state-of-the-art methods.

cs.CV↗

arXiv2019

Fine structure of swift heavy ion track in rutile TiO2

We report on the first observation of fine structure of latent tracks in rutile TiO2, which changes from cylinder to dumbbell-shape and then to sandglass-shape as a function of the ion path length. Based on inelastic thermal spike model, we show that Hagen-Poiseuille flow of molten phase produces the hillocks on surface and the void-rich zone near surface after epitaxial recrystallization due to material deficit, while at a deep depth, the lack of efficient outflow and recrystallization result in the absence of tracks. We propose that core-shell duration of transient molten phase induced by swift heavy ion and parabolic distribution of fluid velocity are radial-dependent. Moreover, the various morphologies of tracks are a consequence of the molten phase outflow and recrystallization during rapid cooling down. Our perspective provides a new interpretation in the track formation.

physics.app-ph↗