Extensive experiments demonstrate the effectiveness and efficiency of the proposed method on several state-of-the-art detection benchmarks.

We thank all the reviewers for their valuable comments and suggestions. We respond to the main concerns as follows. All the source code will be released to the community soon. Q: The authors should report the actual inference time/latency of their models. We evaluate the proposed method on a Tesla V100 GPU.

Roblox wants to make its avatars look less blocky and more realistic, and it has announced a couple of visual updates meant to achieve that goal during its annual developers conference. One of those changes is layered clothing, which it's been working on since at least 2020. It allows any type of character model to be outfitted with layered clothing items. TechCrunch explains that the feature ensures clothing items will fit avatars and will drape around them naturally, whether they're human- or dinosaur-shaped. At the moment, players can only access the feature in the beta version of Roblox Studio's avatar editor, and it's unclear when it'll be more widely available.

The Feature Pyramid Network (FPN) presents a remarkable approach to alleviate the scale variance in object representation by performing instance-level assignments. Nevertheless, this strategy ignores the distinct characteristics of different sub-regions in an instance. To this end, we propose a fine-grained dynamic head to conditionally select a pixel-level combination of FPN features from different scales for each instance, which further releases the ability of multi-scale feature representation. Moreover, we design a spatial gate with the new activation function to reduce computational complexity dramatically through spatially sparse convolutions. Extensive experiments demonstrate the effectiveness and efficiency of the proposed method on several state-of-the-art detection benchmarks.