activity
20162023
most citedDivert More Attention to Vision-Language Tracking

23 citations · 37 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20231 cited

Augment and Criticize: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection

Zhenyu Li, Zhipeng Zhang, Heng Fan +4

In this paper, we improve the challenging monocular 3D object detection problem with a general semi-supervised framework. Specifically, having observed that the bottleneck of this…

cs.CV2023

PlanarTrack: A Large-scale Challenging Benchmark for Planar Object Tracking

Xinran Liu, Xiaoqiong Liu, Ziruo Yi +6

Planar object tracking is a critical computer vision problem and has drawn increasing interest owing to its key roles in robotics, augmented reality, etc. Despite rapid progress, i…

cs.CV2022

High-Fidelity Image Inpainting with GAN Inversion

Yongsheng Yu, Libo Zhang, Heng Fan +1

Image inpainting seeks a semantically consistent way to recover the corrupted image in the light of its unmasked content. Previous approaches usually reuse the well-trained GAN as…

cs.CV202223 cited

Divert More Attention to Vision-Language Tracking

Mingzhe Guo, Zhipeng Zhang, Heng Fan +1

Relying on Transformer for complex visual feature learning, object tracking has witnessed the new standard for state-of-the-arts (SOTAs). However, this advancement accompanies by l…

cs.CV201613 cited

Multi-level Contextual RNNs with Attention Model for Scene Labeling

Heng Fan, Xue Mei, Danil Prokhorov +1

Context in image is crucial for scene labeling while existing methods only exploit local context generated from a small surrounding area of an image patch or a pixel, by contrast l…