Towards holistic understanding of 3D scenes a general 3D segmentation method is needed
that can segment diverse objects without restrictions on object quantity or categories while …

Given a set of calibrated images, Multiple View Stereo (MVS) applies end-to-end depth
inference network to recover scene structure. However, previous methods designed pixel …

The rapid advances of high-performance sensation empowered gigapixel-level
imaging/videography for large-scale scenes, yet the abundant details in gigapixel images …

Recently, various methods have been introduced to address the OOD detection problem
with training outlier exposure. These methods usually count on discriminative softmax metric …

Autoregressive transformers have revolutionized generative models in language processing
and shown substantial promise in image and video generation. However, these models face …

Efficient and precise forest surveys are crucial for in-depth understanding of the present
state of forest resources and conducting scientific forest management. Close-range …

Self-supervised multi-view stereopsis (MVS) attracts increasing attention for learning dense
surface predictions from only a set of images without onerous ground-truth 3D training data …

Decomposing a scene into its 3D geometry, surface material textures, and illumination is a
challenging but important problem in computer vision and graphics. While recent neural …

Multi-view stereopsis (MVS) recovers 3D surfaces by finding dense photo-consistent
correspondences from densely sampled images. In this paper, we tackle the challenging …

The ambiguity at the boundaries of different semantic classes in point cloud semantic
segmentation often leads to incorrect decisions in intelligent perception systems, such as …