Neural Radiance Field (NeRF) has recently become a significant development in the field of
Computer Vision, allowing for implicit, neural network-based scene representation and …

Many tasks in smart agriculture have further requirements for the autonomous navigation of
agricultural robots. Due to irreplaceable visual information and low-cost hardware costs …

The tremendous success of CLIP (Radford et al., 2021) has promoted the research and
application of contrastive learning for vision-language pretraining. In this work, we construct …

Learning visual representations from natural language supervision has recently shown great
promise in a number of pioneering works. In general, these language-augmented visual …

Full-image dependencies provide useful contextual information to benefit visual
understanding problems. In this work, we propose a Criss-Cross Network (CCNet) for …

Perception plays a crucial role in various robot applications. However existing well-
annotated datasets are biased towards autonomous driving scenarios while unlabelled …

Datasets drive vision progress, yet existing driving datasets are impoverished in terms of
visual content and supported tasks to study multitask learning for autonomous driving …

Datasets drive vision progress and autonomous driving is a critical vision application, yet
existing driving datasets are impoverished in terms of visual content. Driving imagery is …

Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision
avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable …

The demand of applying semantic segmentation model on mobile devices has been
increasing rapidly. Current state-of-the-art networks have enormous amount of parameters …