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Found 11 papers, 6 papers with code
A Review and Efficient Implementation of Scene Graph Generation Metrics
Scene graph generation has emerged as a prominent research field in computer vision, witnessing significant advancements in the recent years.
Adapting the Segment Anything Model During Usage in Novel Situations
The interactive segmentation task consists in the creation of object segmentation masks based on user interactions.
Towards Learning Monocular 3D Object Localization From 2D Labels using the Physical Laws of Motion
We present a novel method for precise 3D object localization in single images from a single calibrated camera using only 2D labels.
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data
STOIC2021 consisted of a Qualification phase, where participants developed challenge solutions using 2000 publicly available CT scans, and a Final phase, where participants submitted their training methodologies with which solutions were trained on CT scans of 9724 subjects.
Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance
In order to tell our network which object to segment, we provide the network with a single click on the object's surface on the pseudo depth map of the image as input.
All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes
Performance analyses based on videos are commonly used by coaches of athletes in various sports disciplines.
Detecting Arbitrary Keypoints on Limbs and Skis with Sparse Partly Correct Segmentation Masks
We analyze different training techniques for freely selected and standard keypoints, including pseudo labels, and show in our experiments that only a few partly correct segmentation masks are sufficient for learning to detect arbitrary keypoints on limbs and skis.
Uplift and Upsample: Efficient 3D Human Pose Estimation with Uplifting Transformers
The state-of-the-art for monocular 3D human pose estimation in videos is dominated by the paradigm of 2D-to-3D pose uplifting.
COVID Detection and Severity Prediction with 3D-ConvNeXt and Custom Pretrainings
We introduce a neural network for the prediction of the severity of lung damage and the detection of a COVID-infection using three-dimensional CT-data.
Recognition of Freely Selected Keypoints on Human Limbs
Nearly all Human Pose Estimation (HPE) datasets consist of a fixed set of keypoints.
Extended Self-Critical Pipeline for Transforming Videos to Text (TRECVID-VTT Task 2021) -- Team: MMCUniAugsburg
For both models, we train on the complete VATEX dataset and 90% of the TRECVID-VTT dataset for pretraining while using the remaining 10% for validation.
