Zero-Shot Object Detection
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Benchmarks
LVIS v1.0 minival
LVIS v1.0 val
MS-COCO
MSCOCO
PASCAL VOC'07
ODinW
ImageNet Detection
Most implemented
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models
Learning Open-World Object Proposals without Learning to Classify
Zero-Shot Instance Segmentation
Papers
Does Your VFM Speak Plant? The Botanical Grammar of Vision Foundation Models for Object Detection
Vision foundation models (VFMs) offer the promise of zero-shot object detection without task-specific training data, yet their performance in complex agricultural scenes remains highly sensitive to text prompt constructi…
Zero-Shot Object DetectionPrompt EngineeringPET-DINO: Unifying Visual Cues into Grounding DINO with Prompt-Enriched Training
Open-Set Object Detection (OSOD) enables recognition of novel categories beyond fixed classes but faces challenges in aligning text representations with complex visual concepts and the scarcity of image-text pairs for ra…
Zero-Shot Object DetectionTinyVLM: Zero-Shot Object Detection on Microcontrollers via Vision-Language Distillation with Matryoshka Embeddings
Zero-shot object detection enables recognising novel objects without task-specific training, but current approaches rely on large vision language models (VLMs) like CLIP that require hundreds of megabytes of memory - far…
Zero-Shot Object DetectionRobust Object Detection with Pseudo Labels from VLMs using Per-Object Co-teaching
Foundation models, especially vision-language models (VLMs), offer compelling zero-shot object detection for applications like autonomous driving, a domain where manual labelling is prohibitively expensive. However, thei…
Zero-Shot Object DetectionRobust Object DetectionAutonomous DrivingA Computer Vision Pipeline for Individual-Level Behavior Analysis: Benchmarking on the Edinburgh Pig Dataset
Animal behavior analysis plays a crucial role in understanding animal welfare, health status, and productivity in agricultural settings. However, traditional manual observation methods are time-consuming, subjective, and…
Zero-Shot Object DetectionFine-Grained Zero-Shot Object Detection
Zero-shot object detection (ZSD) aims to leverage semantic descriptions to localize and recognize objects of both seen and unseen classes. Existing ZSD works are mainly coarse-grained object detection, where the classes …
Zero-Shot Object Detection