11 skills found
prs-eth / ResDepth[ISPRS Journal of Photogrammetry and Remote Sensing, 2022] ResDepth: A Deep Residual Prior For 3D Reconstruction From High-resolution Satellite Images
IRMVLab / DifFlow3D[CVPR 2024, TPAMI 2025] DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Iterative Diffusion-Based Refinement
aluo-x / 3D SLNOfficial code for "End-to-End Optimization of Scene Layout" -- including VAE, Diff Render, SPADE for colorization (CVPR 2020 Oral)
dfuentes-uah / DPDnet A Robust People Detector Using Deep Learning With An Overhead Depth CameraThis paper proposes a deep learning-based method to detect multiple people from a single overhead depth image with high precision. Our neural network, called DPDnet, is composed by two fully-convolutional encoder-decoder blocks built with residual layers. The main block takes a depth image as input and generates a pixel-wise confidence map, where each detected person in the image is represented by a Gaussian-like distribution, The refinement block combines the depth image and the output from the main block, to refine the confidence map. Both blocks are simultaneously trained end-to-end using depth images and ground truth head position labels. The paper provides a rigorous experimental comparison with some of the best methods of the state-of-the-art, being exhaustively evaluated in different publicly available datasets. DPDnet proves to outperform all the evaluated methods with statistically significant differences, and with accuracies that exceed 99%. The system was trained on one of the datasets (generated by the authors and available to the scientific community) and evaluated in the others without retraining, proving also to achieve high accuracy with varying datasets and experimental conditions. Additionally, we made a comparison of our proposal with other CNN-based alternatives that have been very recently proposed in the literature, obtaining again very high performance. Finally, the computational complexity of our proposal is shown to be independent of the number of users in the scene and runs in real time using conventional GPUs.
ShaoqLin / DiscoSG[EMNLP 2025 Outstanding Paper Award] Official repo for DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinement
raushan202000 / Image Dehazing By Artificial Multiple Exposure Image FusionBad weather conditions can reduce visibility on images acquired outdoors, decreasing their visual qual- ity. The image processing task concerned with the mitigation of this effect is known as image dehaz- ing. In this paper we present a new image dehazing technique that can remove the visual degradation due to haze without relying on the inversion of a physical model of haze formation, but respecting its main underlying assumptions. Hence, the proposed technique avoids the need of estimating depth in the scene, as well as costly depth map refinement processes. To achieve this goal, the original hazy image is first artificially under-exposed by means of a sequence of gamma-correction operations. The resulting set of multiply-exposed images is merged into a haze-free result through a multi-scale Laplacian blend- ing scheme. A detailed experimental evaluation is presented in terms of both qualitative and quantitative analysis. The obtained results indicate that the fusion of artificially under-exposed images can effectively remove the effect of haze, even in challenging situations where other current image dehazing techniques fail to produce good-quality results.
dornik / SporeagentSporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement
arghyasur1991 / QuestRoomScanReal-time 3D room reconstruction on Meta Quest 3. GPU TSDF + Surface Nets meshing, passthrough texturing, on-device texture refinement with Sobel normals, AI object detection (YOLO/Sentis + GPU NMS), MRUK scene understanding, Gaussian Splat training & rendering, multi-scan persistence with spatial anchors. Unity 6 URP package.
gavin-gqzhang / BiRefBiRef: Bimodal Predicate Refinement with Decoupled Entity-Predicate Representations for Scene Graph Generation
QiuDeZhang / MonoDTFRevisiting Monocular 3D Object Detection from Scene-Level Depth Retargeting to Instance-Level Spatial Refinement
divinrkz / Agentic Scene GraphA pipeline demonstrating how successive refinements of an intermediate scene-graph JSON lead to more robust 3D scene synthesis.
