Search Results for author:
Found 6 papers, 3 papers with code
SketchBodyNet: A Sketch-Driven Multi-faceted Decoder Network for 3D Human Reconstruction
Compared with natural images, freehand sketches are much more flexible to depict various shapes, providing a high potential and valuable way for 3D human reconstruction.
CrowdMLP: Weakly-Supervised Crowd Counting via Multi-Granularity MLP
Existing state-of-the-art crowd counting algorithms rely excessively on location-level annotations, which are burdensome to acquire.
Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory Tracing
For the vehicle detection and tracking module, we adopted YOLOv5 and multi-scale tracking to localize the anomalies.
STNet: Scale Tree Network with Multi-level Auxiliator for Crowd Counting
To battle the ingrained issue of accuracy degradation, we propose a novel and powerful network called Scale Tree Network (STNet) for accurate crowd counting.
Interlayer and Intralayer Scale Aggregation for Scale-invariant Crowd Counting
Crowd counting is an important vision task, which faces challenges on continuous scale variation within a given scene and huge density shift both within and across images.
BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image Synthesis
The key feature of BSD-GAN is that it is trained in multiple branches, progressively covering both the breadth and depth of the network, as resolutions of the training images increase to reveal finer-scale features.
