6 accepted papers
We present a novel dual-end complementary method for online depth estimation and mesh reconstruction, termed DepthMesh. Unlike most existing state-of-the-art methods that produce either only depth online or surface mesh offline, our method tightly couples online multiview depth estimation and Trunca…
Our world faces the challenge of efficiently and responsibly managing the ever-growing volume of urban waste. Many countries and regions have implemented categorized trash bins and require residents to sort their waste according to specified criteria. Proper waste classification by residents signifi…
Three-dimensional object detection is one of the key tasks in autonomous driving. To reduce costs in practice low-cost multi-view cameras for 3D object detection are proposed to replace the expansive LiDAR sensors. However relying solely on cameras is difficult to achieve highly accurate and robust…
Conventional text-to-SQL studies are limited to a single task with a fixed-size training and test set. When confronted with a stream of tasks common in real-world applications, existing methods struggle with the problems of insufficient supervised data and high retraining costs. The former tends to…
On the WikiSQL benchmark, most methods tackle the challenge of text-to-SQL with predefined sketch slots and build sophisticated sub-tasks to fill these slots. Though achieving promising results, these methods suffer from over-complex model structure. In this paper, we present a simple yet effective…
Stochastic recurrent neural networks have shown promising performance for modeling complex sequences. Nonetheless, existing methods adopt KL divergence as distribution regularizations in their latent spaces, which limits the choices of models for latent distribution construction. In this paper, we i…