7 accepted papers
3D dense captioning aims to describe the crucial regions in 3D visual scenes in the form of natural language. Recent prevailing approaches achieve promising results by leveraging complicated structures incorporated with large-scale models, which necessitate abundant parameters and pose challenges re
Autonomous navigation in open-world outdoor environments faces challenges in integrating dynamic conditions, long-distance spatial reasoning, and semantic understanding. Traditional methods struggle to balance local planning, global planning, and semantic task execution, while existing large languag
Recently, camera localization has been widely adopted in autonomous robotic navigation due to its efficiency and convenience. However, autonomous navigation in unknown environments often suffers from scene ambiguity, environmental disturbances, and dynamic object transformation in camera localizatio
Group Equivariant Convolution (GConv) can capture rotational equivariance from original data. It assumes uniform and strict rotational equivariance across all features as the transformations under the specific group. However, the presentation or distribution of real-world data rarely conforms to str…
Weakly supervised referring expression grounding (WREG) is an attractive and challenging task for grounding target regions in images by understanding given referring expressions. WREG learns to ground target objects without the manual annotations between image regions and referring expressions durin…
Weakly supervised referring expression grounding aims to train a model without the manual labels between image regions and referring expressions during the training phase. Current predominant models often adopt deep structures to reconstruct the region-expression correspondence. A crucial deficiency…
Domain adaptation methods are used to address a problem, in which train scenario (source domain) and test scenario (target domain) are different. The existing methods mainly perform adaptation via reducing domain discrepancy from the view of a probability distribution. However, the idea of probabili…