49 skills found · Page 1 of 2
microsoft / TrillTrill is a single-node query processor for temporal or streaming data.
temporalio / Temporalite ArchivedAn experimental distribution of Temporal that runs as a single process
bmartacho / UniPoseWe propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datasets demonstrate that UniPose, with a ResNet backbone and Waterfall module, is a robust and efficient architecture for pose estimation obtaining state-of- the-art results in single person pose detection for both sin- gle images and videos.
Z-Zheng / ChangeStarChange is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery (ICCV 2021) https://arxiv.org/abs/2108.07002
zkawfanx / StableLLVELearning Temporal Consistency for Low Light Video Enhancement from Single Images (CVPR2021)
shyamal-b / Ss TadEnd-to-End, Single-Stream Temporal Action Detection in Untrimmed Videos (Official Repo for SS-TAD)
shyamal-b / SstSST: Single-Stream Temporal Action Proposals (Official Repo)
HYPJUDY / Decouple SSADDecoupling Localization and Classification in Single Shot Temporal Action Detection
ranjaykrishna / SSTSST: Single-Stream Temporal Action Proposal
ceva-ip / DPDFNetDPDFNet: causal single-channel speech enhancement that boosts DeepFilterNet2 with dual-path RNN blocks for stronger long-range temporal and cross-band modeling. Repo includes PyTorch implementation + checkpoints, ONNX & TFLite models with inference code, and a real-time demo.
Media-Smart / VedatadA single stage temporal action detection toolbox based on PyTorch
JaehaKim97 / BlurHand RELEASEOfficial implementation of the paper "Recovering 3D Hand Mesh Sequence from a Single Blurry Image: A New Dataset and Temporal Unfolding" (CVPR 2023)
JaywongWang / SST TensorflowTensorflow Implementation of the Paper "SST: Single-Stream Temporal Action Proposals" in CVPR 2017.
ChenHongruixuan / I3PE[ISPRS J P&RS 2023] Exchange means change: an unsupervised change detection framework based on intra- and inter-image patch exchange
koujan / Robotics Course ProjectHaze can cause poor visibility and loss of contrast in images and videos. In this article, we study the dehazing problem which can improve visibility and thus help in many computer vision applications. An extensive comparison of state of the art single image dehazing methods is done. One simple contrast enhancement method is used for dehazing. Structure- texture decomposition has been used in conjunction with this enhancement method to improve its performance in presence of synthetic noise. Methods which use a haze formation model and attempt at solving an ill-posed problem using computer vision priors are also investigated. The two priors studied are dark channel prior and the non-local prior. Both qualitative and quantitative comparisons for atmospheric and underwater images on all three methods provide a conclusive idea of which dehazing method performs better. All this knowledge has been extended to video dehazing. A video dehazing method which uses the spatial and temporal information in a video is studied in depth. An improved version of video dehazing is proposed in this article, which uses the spatial-temporal information fusion framework but does not suffer from some of its limitations. The new video dehazing method is shown to produce better results on test videos
Gregjksmith / Single Image Example Based Super ResolutionSingle image example-based super resolution. Improves the spatial and temporal resolution of an image using a direct mapping of LR HR patch pairs. C++, openCV.
gist-ailab / IITNet OfficialThis is an official implementation for "Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG".
anaslimem / CortexaDBIt is a simple, fast, and hard-durable embedded database designed specifically for AI agent memory. It provides a single-file-like experience (no server required) but with native support for vectors, graphs, and temporal search.
tukilabs / Video Compression NetA new approach to video compression by refining the shortcomings of conventional approach and substituting each traditional component with their neural network counterpart. Our proposed work consists of motion estimation, compression and compensation and residue compression, learned end-to-end to minimize the rate-distortion trade off. The whole model is jointly optimized using a single loss function. Our work is based on a standard method to exploit the spatio-temporal redundancy in video frames to reduce the bit rate along with the minimization of distortions in decoded frames. We implement a neural network version of conventional video compression approach and encode the redundant frames with lower number of bit.
rsinghlab / ScNODEscNODE: Generative Model for Temporal Single Cell Transcriptomic Data Prediction
