← Back to all news
arXiv Computer Vision By Alfonso L\'opez-Ruiz, Diego Royo

Memory-efficient GPU pipelines for real-time non-line-of-sight reconstruction

Read the original on arXiv Computer Vision →

The paper presents memory‑efficient GPU pipelines that accelerate real‑time non‑line‑of‑sight (NLOS) reconstruction. By redesigning two wave‑based algorithms—f‑k migration and phasor‑fields—with fused kernels, warp‑level photon binning, batched transforms, CUDA graph replay, and selective FP16 storage, the authors achieve up to 42× speed‑ups over a reference streaming pipeline and 14× over the fastest published GPU baseline while reducing memory usage to as little as 2.5%. The work also includes an ablation study of implementation choices and introduces three denoising strategies that leverage the increased frame budget for future NLOS video processing.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

Related stories

arXiv Machine Learning
Jun 30

Efficient 3D Gaussian Splatting with Axis-Shared Rasterization and Order-independent Transmittance

arXiv:2506. 07069v2 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, combining high-quality reconstruction with efficient rendering.

By Zhican Wang, Guanghui He, Lingjun Gao, Dantong Liu, Shell Xu Hu, Chen Zhang, Zhuoran Song, Nicholas Lane, Hongxiang Fan
agentsroboticsbenchmarks
More like this →
arXiv Computer Vision
Sep 22

SparkDiffusion: Mitigating the High-Sparsity Trap --- A Unified Framework for up to $265\times$ Single-GPU Acceleration of Visual Generation

arXiv:2609.23153v1 Announce Type: new Abstract: Video diffusion transformers are expensive because attention dominates long spatiotemporal token sequences. We identify the \emph{high-sparsity trap}:...

By Yuxi Liu, Haoyu Li, Zekun Zhang, Tengxu Sun, Yixiang Cai, Jiayong Li, Yifei Xia, Tianle Liu, Baole Ai, Ang Wang, Jiamang Wang, Lin Qu, Kai Zhang, Kun Yuan, Bin Cui
llmsdiffusionefficiency
More like this →
arXiv Computer Vision
Sep 22

RegVGGT: Sustainable Visual Geometry Grounding for Streaming via Regulated Memory

arXiv:2609.23286v1 Announce Type: new Abstract: 3D reconstruction from a lengthy video stream input poses a dilemma for feed-forward reconstruction models (FFRMs), that a whole-stream inference conte...

By Hongbo Mao (Harbin Institute of Technology), Junjun Jiang (Harbin Institute of Technology), Youyu Chen (Harbin Institute of Technology), Jiaxin Zhang (Harbin Institute of Technology), Zhemeng Dong (Harbin Institute of Technology), Xianming Liu (Harbin Institute of Technology)
benchmarks
More like this →
arXiv AI
Oct 9

The Operator Mismatch Problem: Deploying BEV Perception with Portable GPU Compute

The paper introduces BEVPIPE, a framework that enables deployment of bird's-eye-view (BEV) perception models—used in autonomous driving to fuse camera and LiDAR data—on portable GPU compute APIs. By partitioning the model into dense subgraphs managed by standard inference runtimes and handling sparse 3D convolutions and geometric scatter operations through external extensions, BEVPIPE achieves a 19.5× speedup while preserving 98.5% of the reference mean average precision. The approach also demonstrates portability across different GPU backends, breaking the current reliance on CUDA-only, PyTorch‑coupled sparse convolution libraries.

By Rohit Verma, Anand V Bodas
agentsroboticsmultimodal
More like this →