Get 3D scene with fewer images by adapting scene priors trained on large datasets with NFP

Real-time unsupervised video object segmentation by training with images and optical flow with TMO

Segment scene in new domain with one image using adversarial refinement with SITTA-SEG

Get 3D object from scene by lifting Segment Anything Model masks into 3D field with NOC

Real-time video object segmentation by using global assignment and semantic features with TCOVIS

3D point cloud segmentation with few examples using shared geometric components with GFS-3DSeg_GWs

Survey of human gait recognition using deep learning

Get 3D scene by using view-dependent colors and constraints on geometry and photography with Yu

Detect object with few examples and hidden parts by extending local to co-existing regions with ECEA

Get camera position from image and 3D point clouds by match image patch to points with EP2P-Loc

Get 3D scene using multiple priors and regularizers with Lincetto

Detect object by train on text-to-image for foreground and background with Text2Image-for-Detection

Survey of small object detection using transformers

Segment object in video from text description by global information from object queries with TempCD

Get 3D object shape from one image by synchronizing generated images of many views with SyncDreamer

Complete 3D scene by fusion of depth and color features at different scales with AGG-Net

Real-time 3D scene reconstruction from monocular, stereo, RGB-D input using all history with GO-SLAM

Detect unknown objects using unsupervised region proposal methods with MEPU

Get 3D scene from one image by using the distances between points in a latent space with SQLdepth

Segment unknown object match text description by generative and discriminative models with Ref-Diff