Latest Object Detection Research Papers

The newest Object Detection papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Object Detection so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.

Recent papers

• Improved Lightweight Object Detection Network for Brain Tumor Detection
  Binying FAN, Zhen CUI, Xia WANG · DOAJ (DOAJ: Directory of Op... · Nov 1, 2026

  Objective:This study aimed to enhance the detection efficiency of brain tumor images by optimizing the lightweight real-time object detection model YOLOv7-tiny, proposing an improved framework tailored for brain tumor detection tasks. Metho…

• FastBEVFusion: Simple Multi-Modal Fusion for 3D Object Detection at 50 FPS
  Tom Sanitz, Emre Gülsoylu, Simone Frintrop, Christian Wilms · arXiv · Oct 27, 2026

  Reliable real-time 3D object detection based on LiDAR and camera data is critical for safety in autonomous driving, where systems must accurately perceive their surroundings with minimal latency. Many state-of-the-art systems achieve high-q…

• Semantic-based Synthetic Data Generation for Object Detection under Data Scarcity
  Byunghyun Kim, Seongyun Jeong, Sangyoung Park, Bumkyu Choi et al. · 정보과학회 컴퓨팅의 실제 논문지 · Oct 27, 2026
• VPR-Space: A Benchmark for Visual Place Recognition in Space Analog Domains
  Richard Fechner, Peer Neubert · arXiv · Oct 26, 2026

  Visual Place Recognition (VPR) is an important means for loop closure detection in visual Simultaneous Localization and Mapping (SLAM). While state-of-the-art VPR and SLAM approaches excel in urban and feature-rich natural environments, the…

• OBB-PBD: Extending Parallel Box Decoding to Oriented Bounding Boxes for Referring Expression Grounding in Aerial Imagery
  Chang Woo Song, Yeong Jun Koh · arXiv · Oct 26, 2026

  Referring expression grounding in overhead imagery requires oriented bounding boxes rather than horizontal ones, since aerial objects appear at arbitrary orientations. Most grounding models emit box coordinates sequentially; Parallel Box De…

• GIFT: Representation Geometry Matters for Single-Domain Generalized Object Detection
  Yin Zhang, Yaoyue Zheng, Yongqiang Zhang, Bogdan Raducanu et al. · arXiv · Oct 26, 2026

  Single-Domain Generalized Object Detection (S-DGOD) aims to generalize from a single source domain to unseen domains under distribution shifts. Existing efforts mainly focus on simulating unseen domains or suppressing domain-specific factor…

• Analysis of Train–Validation Dependence and Evaluation Reliability in a Video-Derived Object Detection Dataset
  Seungjin Kim · Journal of the Institute of... · Oct 26, 2026
• Object detection and approximate boundary extraction using deep learning-based patch classification and curve evolution
  Amine Iziy, Ali Tavakoli, Mostafa Eslami · The Visual Computer · Oct 26, 2026
• WeVisOne-VL: Unified Visual Perception from Objects to Pixels
  Tianming Liang, Junyi Pan, Yuxi Li, Canmiao Fu et al. · arXiv · Oct 22, 2026

  Existing vision-language models (VLMs) remain unreliable for fine-grained visual perception. In this report, we present WeVisOne-VL (WeChat Vision All-in-One), a powerful VLM that unifies object-level and pixel-level perception through stru…

• Compositionality with Primitives: A Unified View from Euclidean to Hyperbolic Vision-Language Models
  Puru Vaish, Meelad Dashti, Christoph Brune, Pascal Mettes et al. · arXiv · Oct 21, 2026

  Compositional zero-shot learning (CZSL) aims to recognize novel combinations of previously observed objects and attributes. Prior work showed that large-scale vision-language models encode decomposable semantic structures that can be recomp…

• Open-Vocabulary Models and Label Propagation for Uncertainty-aware Pseudo-Labeling of Object Detection Datasets
  Jonathan Klees, Timo Heller, Matthias Rottmann · arXiv · Oct 21, 2026

  Object detection models rely on large-scale annotated datasets that require substantial manual annotation effort. The labeling costs further increase when annotation uncertainty is captured through soft labels, as multiple annotations must …

• FogTTA: Online Test-Time Adaptation for Robust Transformer-based Object Detection in Foggy Weather
  Ali Abedi, Q. M. Jonathan Wu, Ning Zhang, Shiqi Tian · arXiv · Oct 21, 2026

  Object detection models for autonomous driving commonly experience substantial performance drops when deployed under adverse weather due to the domain shift between training data and real-world operating conditions. This degradation is espe…

• Application of a neural network approach to the recognition of guiding triangles on oil and gas field diagrams
  A. S. Abaturov · INFORMACIONNYE TEHNOLOGII · Oct 21, 2026

  The article is devoted to methods for automated recognition of guiding triangles on engineering diagrams of oil and gas fields. Recognition here refers to the detection, localization, and classification of these graphic objects; the output …

• Copyright Leakage Detection in AI Generated Videos
  Shaif Chowdhury, Moshiur Rahman Tonmoy · arXiv · Oct 20, 2026

  Video generation models can create realistic-looking video footage from images and text prompts. Some of the recent advances have raised concerns about the reproduction of copyrighted visual content. However, copyright leakage detection in …

• CLOSER: Evidence-Aware Active Visual Verification for Embodied Object-Goal Navigation
  Pengying Wu, Mingye Jiang, Yunze Hu, Zhejia Wen et al. · arXiv · Oct 20, 2026

  Object-goal navigation (ObjectNav) requires an embodied agent to find an instance of a specified category in an unseen environment and stop near it. The agent typically relies on an object detector but must judge online from a limited egoce…

• GALA: Geometry-Aware Language Model for Controllable Object Arrangement
  Chucheng Xiang, Runze Wang, Zhi Deng, Ruchao Bao et al. · arXiv · Oct 20, 2026

  Reasoning about fine-grained placement constraints, such as support and containment, is essential for realistic 3D scene creation. It remains a significant challenge for existing methods that rely on simplified object representations like o…

• End-to-end object detection enhanced by hierarchical convolution modulation and sparse attention transmission
  Lixin He, Guangzhuang Yao, Zhi Cheng, Xiaofeng Wang et al. · Signal Image and Video Proc... · Oct 20, 2026
• Application of YOLOv11s Algorithm to Automate Egg Counting in Poultry Farms
  Muh. Hakkam Zakka Robbani, Akhfa Bagas Alfarizi, Adrian Fardan Andi, Gema Parasti Mindara et al. · Journal of Information Engi... · Oct 18, 2026

  Chicken eggs are a strategic food commodity and a globally affordable source of animal protein. In the industrial poultry farming sector, accurate daily production data is fundamental for evaluating biological performance, feed efficiency, …

• An underwater object detection method based on generative degradation simulation and hard-sample learning
  Feng Wang, Baorong Zhan, Shaojiang Liu, Fang Deng et al. · Scientific Reports · Oct 18, 2026

  Underwater images are affected by spectral attenuation, particulate scattering, and nonuniform illumination and therefore often exhibit color shifts, reduced contrast, blurred edges, and local darkening. Existing public datasets provide lim…

• YOLO11-DAL a multi-scale fusion network for target detection in UAV-based power line inspection
  Taotao Wu, Zhonghua Liu · Scientific Reports · Oct 17, 2026

  Abstract Reliable detection of transmission-line components and defects in unmanned aerial vehicle (UAV) imagery supports preventive maintenance. Repeated downsampling, however, removes fine spatial detail, while limited interaction between…

• An Efficient Approach to Beetle Damage Detection of Banana Using Deep Learning
  Md. Mehedi Hasan Naeem, Ishtiyak Ahmmad Araf, Md. Arefin Haque Mahir, Tushar Kanti Saha · arXiv · Oct 16, 2026

  Visible surface damage of banana fruits by Basilepta subcostata (the banana fruit scarring beetle) can reduce their market value. Here, manual inspection of Banana fruits is subjective and difficult to scale. This study presents a lightweig…

• Quantifying Annotation Agreement in Object Detection with Optimal Transport
  Kirill Prokhorov, Alexandr A. Kalinin · arXiv · Oct 14, 2026

  Reliable validation of machine learning models is a crucial step in designing robust and trustworthy systems. Yet validation relies on annotated test sets treated as ground truth, even though annotations can be noisy or ambiguous. In object…

• Lightweight Self-reconstruction-based Feature Enhancement Framework for Real-time Small Object Detection
  Gyeongseo Kim, Han-Sol Kim · Journal of Institute of Con... · Oct 14, 2026
• A Study on Efficient BEV Transformation via Image Compression and Performance Enhancement of Transformer-based 3D Object Detection
  HanKyeol Yu, Seungjin Jung, Kyeongjae Ahn, Yeonsik Kang · Journal of Institute of Con... · Oct 14, 2026
• Context-aware Bayesian Fusion for Multimodal Object Detection
  Arunachalam Venkatachalam, Mhafuzul Islam, Marwan Yusuf, David Van Hamme et al. · arXiv · Oct 13, 2026

  Reliable detection of pedestrians and road users is essential for the safe operation of autonomous vehicles. However, this task becomes increasingly challenging under adverse environmental conditions, such as poor weather and low lighting, …

• CryoTracer: A Synthetic-to-Real System for Filament Instance Tracing in Cryo-EM
  Radosław Kuczbański, Wojciech Kozłowski, Mateusz Grzesiuk, Konrad Karanowski et al. · arXiv · Oct 13, 2026

  Particle picking in cryo-electron microscopy is commonly formulated as an object-detection problem in which individual particles are represented by bounding boxes, a natural representation for globular particles but a poor match for filamen…

• Resource-Efficient 3D Shape and Orientation Estimation of Road Users using Roadside RGB Camera and 3D Radar
  Shiva Agrawal, Savankumar Bhanderi, Gordon Elger · arXiv · Oct 13, 2026

  End-to-end deep learning pipelines for camera-radar 3D object detection are well established in driver assistance systems and autonomous vehicles; however, adapting them to roadside-mounted infrastructure presents significant challenges. On…

• BENCHMARKING 2D AND 3D OBJECT DETECTION MODELS ON DIFFERENT EDGE COMPUTING PLATFORMS
  SHAHLA URALOVA, Amil Babayev, Qurban YUSUFOV, Rasim Mahmudov · JOURNAL OF BAKU ENGINEERING... · Oct 12, 2026

  The deployment of artificial intelligence models on edge computing platforms is imperative for applications necessitating real-time perception, including object detection and gesture recognition.This paper presents a thoroughgoing benchmark…

• Multi-scale Feature Enhanced Network for Remote Sensing Object Detection
  Yanyan Zang, 丁学文 Ding Xuewen, Yuchen Jiang, Zewen Zi · Frontiers in Computing and ... · Oct 10, 2026

  The task of remote sensing image target detection still faces many challenges: the target scale, orientation and spatial distribution are very different. In particular, small targets are difficult to identify in complex backgrounds, and the…

• Selective Fuzzy Bytetrack: An Association-Level Fuzzy Enhancement For Multi-Object Pedestrian Tracking
  B. B. Aboud, M. Alabbas, H. Z. Neima · African Journal Of Applied ... · Oct 10, 2026

  Purpose: This study aims to improve pedestrian identity preservation in crowded multi-object tracking by enhancing ByteTrack's association stage without modifying the detector. The focus is on reducing incorrect detection-to-track assignmen…