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Sponsored by
ThumbnailCreator.com
litert-community / L2CS-Gaze360-LiteRT
Model's Last Updated: September 08 2026
image-classification
Introduction of L2CS-Gaze360-LiteRT
Model Details of L2CS-Gaze360-LiteRT
L2CS-Net — LiteRT (on-device gaze estimation, fully-GPU)
L2CS-Net
(Ahmednull) gaze estimation, converted to
LiteRT
and
running
fully on the
CompiledModel
GPU
(ML Drift) on Android. Predicts where a centered face is looking
(yaw/pitch). ResNet50 backbone trained on Gaze360.
On-device (Pixel 8a, Tensor G3 — verified)
| nodes on GPU | 139 / 139 LITERT_CL (full residency) |
| inference | ~3 ms (448×448) |
| size | 47.9 MB (fp16) |
| accuracy | device-vs-PyTorch corr 0.9999 , gaze angle within ~0.1° |
face[1,3,448,448] (ImageNet-normalized) →[GPU: ResNet50]→ yaw[1,90], pitch[1,90] (softmax over angle bins)
The 90 bins span [-180,180]° (4° each); gaze angle = softmax expectation
Σ p_i·i · 4 − 180
(softmax baked in).
How it converts (litert-torch)
Pure CNN (ResNet50 + 2 FC heads). Two numerically-exact ResNet fixes:
-
stem
MaxPool2d(3,s2,p1)→ zero-pad + valid max-pool — PyTorch's max-pool pads with-inf→ aPADV2the Mali delegate won't delegate (compile fail); since the pool follows a ReLU, a 0-pad is exactly equivalent →PAD, full GPU residency. -
global
AdaptiveAvgPool2d(1)→mean(3).mean(2).
Result: banned ops NONE, all tensors ≤4D, tflite-vs-torch corr 1.0 , device-vs-torch corr 0.9999 .
Preprocessing & decode
Center-crop to a (centered) face, resize 448×448, /255, ImageNet mean/std, NCHW. Decode: softmax expectation over the 90 bins → yaw/pitch degrees → gaze direction.
License
MIT . Upstream: Ahmednull/L2CS-Net .
Runs of litert-community L2CS-Gaze360-LiteRT on huggingface.co
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More Information About L2CS-Gaze360-LiteRT huggingface.co Model
Url of L2CS-Gaze360-LiteRT
L2CS-Gaze360-LiteRT huggingface.co Url
Provider of L2CS-Gaze360-LiteRT huggingface.co
Other API from litert-community
Updated:August 31 2026
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