Mar 13, 2024 · Due to the addition of a camera movement module, our model can better track salient object in egocentric videos with unique camera movements.

Experimental results show that the approach outperforms other state-of-the-art methods in egocentric video salient object detection tasks. Dataset and codes can ...

Mar 1, 2024 · Experimental results show that the approach outperforms other state‐of‐the‐art methods in egocentric video salient object detection tasks.

Experimental results show that the approach outperforms other state‐of‐the‐art methods in egocentric video salient object detection tasks. Dataset and codes can ...

Experimental results show that the approach outperforms other state‐of‐the‐art methods in egocentric video salient object detection tasks. Dataset and codes can ...

In this paper we propose a Deep CNN approach and the general framework for recognition of objects in a real-time scenario and in an egocentric perspective.

Jun 23, 2016 · In this paper we propose a Deep CNN approach and the general framework for recognition of objects in a real-time scenario and in an egocentric ...

Aug 7, 2024 · Objects that move relative to the camera are often more salient and easier to identify. By analyzing motion patterns, the model can learn to ...

In this paper we propose a Deep CNN approach and the general framework for recognition of objects in a real-time scenario and in an egocentric perspective. Here ...

The intra- frame contrastive loss helps separate the foreground and background features, and the inter-frame contrastive loss improves the temporal consistency.