Lvis
PulseAugur coverage of Lvis — every cluster mentioning Lvis across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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New study "Robust Onion" analyzes noise impact on object detectors
A new study titled "Robust Onion" investigates the impact of real-world noise on Open Vocabulary Object Detectors (OV-ODs). The research uses controlled synthetic degradations to analyze how and why these detectors lose…
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PicoSAM3 model enables real-time segmentation on image sensors
Researchers have developed PicoSAM3, a new lightweight segmentation model designed for real-time execution on edge devices and even directly on image sensors. This model, with 1.3 million parameters, utilizes a dense CN…
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New framework uses scene graphs for open-vocabulary object detection
Researchers have developed a new framework for open-vocabulary object detection that leverages scene graphs to understand relationships between objects. This approach aims to improve the identification of novel object c…
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FlowOVD paper introduces generative latent flows for open-vocabulary detection
Researchers have introduced FlowOVD, a novel approach to open-vocabulary object detection that reframes the problem from a discriminative to a generative one. This method utilizes a continuous transport process in laten…
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Ultralytics YOLO26 advances real-time vision with NMS-free design
Ultralytics has introduced YOLO26, a new family of real-time vision models designed to overcome limitations in existing YOLO detectors. This new model features a dual-head design for NMS-free inference and removes Distr…
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CaptionFormer model unifies video object tracking and captioning
Researchers have developed CaptionFormer, a novel end-to-end model designed to unify the tasks of object detection, segmentation, tracking, and captioning within videos. To address the challenge of limited annotated dat…
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DETR-ViP enhances visual prompted object detection with discriminative prompts
Researchers have introduced DETR-ViP, a novel framework designed to enhance visual prompted object detection. The method addresses suboptimal performance by focusing on creating class-distinguishable visual prompts, whi…
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VL-SAM-v3 enhances open-world object detection with visual memory
Researchers have introduced VL-SAM-v3, a novel framework designed to enhance open-world object detection by incorporating external visual memory. This approach augments existing methods, which often struggle with fine-g…
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New methods improve open-vocabulary object detection robustness and adaptation
Researchers have introduced several new methods to improve open-vocabulary object detection, a field that aims to identify arbitrary objects based on human prompts. One approach, EBOD, integrates a prompt-based detector…
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New OVD method improves object detection with hierarchical consistency and unbiased objectness
Researchers have developed a new framework to improve open-vocabulary object detection (OVD), a technique that allows AI models to identify objects beyond their training data. The proposed method addresses inaccuracies …